CN113420928A

CN113420928A - Order scheduling method, device, equipment and storage medium

Info

Publication number: CN113420928A
Application number: CN202110734686.7A
Authority: CN
Inventors: 王龙; 杨周龙; 何平
Original assignee: Dongpu Software Co Ltd
Current assignee: Dongpu Software Co Ltd
Priority date: 2021-06-30
Filing date: 2021-06-30
Publication date: 2021-09-21

Abstract

The invention relates to the field of logistics distribution and discloses an order scheduling method, a device, equipment and a storage medium, wherein the method comprises the following steps: splitting or combining a first order to be scheduled in an order set to be scheduled into a second order to be scheduled according to an order splitting rule or an order combining rule; according to the vehicle information and the order information of the second order to be scheduled, route planning is carried out on all vehicles to be scheduled in the vehicle set to be scheduled, and a delivery route corresponding to each vehicle to be scheduled is obtained; calculating the cost of each vehicle to be dispatched for dispatching the second order to be dispatched according to the dispatching route and a preset cost algorithm; and selecting the vehicles to be dispatched from the vehicle set to be dispatched as the delivery vehicles for delivering the second order to be dispatched according to the delivery route cost and the preset constraint condition. According to the method, the vehicle type of the vehicle to be dispatched corresponding to the order is selected according to the cost minimum algorithm strategy under the condition that the timeliness requirement is met through intelligent dispatching, and the optimal distribution scheme is obtained.

Description

Order scheduling method, device, equipment and storage medium

Technical Field

The invention relates to the field of logistics distribution, in particular to an order scheduling method, device, equipment and storage medium.

Background

The distribution time of goods is more and more strict with people shopping online. Resulting in increasingly intense competition among logistics companies. Logistics generally refers to a road transportation method that sequentially takes goods from different suppliers according to a given route and time, and finally sends all the goods to a destination such as a factory or a warehouse. Due to the fact that logistics transportation vehicles need to go to and fro different places to achieve logistics transportation, logistics transportation time is difficult to predict, and logistics scheduling needs to be carried out on the logistics transportation vehicles according to orders. In the traditional logistics scheduling, only a single target is usually considered for optimal loading, the considered constraint conditions are less, the actual needs of business are not reflected, and a scheduling plan is formed simply by planning and allocating orders to vehicles. The scheduling scheme generated by the method mostly adopts feasible solutions, is not an optimal solution, does not comprehensively consider the optimization target, and causes low efficiency and high cost.

Disclosure of Invention

The method and the device mainly aim to solve the technical problem that due to the fact that the pertinence of the screened constraint conditions is low, the order scheduling accuracy is not high in the existing logistics order scheduling scheme.

The first aspect of the present invention provides an order scheduling method, including: acquiring order information of each cargo to be distributed and vehicle information of each distribution vehicle; acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled; judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information; if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to the splitting rule or the combining rule; performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route; sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm; and according to the distribution route cost and preset constraint conditions, intensively screening the vehicles to be dispatched from the vehicles to be dispatched as distribution vehicles for distributing the second orders to be dispatched.

Optionally, in a first implementation manner of the first aspect of the present invention, the order information at least includes a departure address, a destination address, a cargo size, a cargo quantity, and a type of a loaded vehicle, and the determining, according to the order information, whether a first to-be-scheduled order in the to-be-scheduled order set meets one of a preset splitting rule or a preset merging rule includes: judging whether the first order to be scheduled exceeds the bearing upper limit of the bearing vehicle type according to the cargo size and the cargo quantity of the first order to be scheduled; if so, the first order to be scheduled conforms to the splitting rule; if not, judging whether a first order to be scheduled with the same departure place address and the same destination address exists in the order set to be scheduled; and if so, the first order to be scheduled accords with the merging rule.

Optionally, in a second implementation manner of the first aspect of the present invention, the splitting or merging the first to-be-scheduled order in the to-be-scheduled order set into the second to-be-scheduled order according to the splitting rule or the merging rule includes: if a first order to be scheduled in the order set to be scheduled meets the splitting rule, splitting the first order to be scheduled into at least two second orders to be scheduled according to the quantity of the goods, wherein the second order to be scheduled is smaller than the bearing upper limit of the type of the borne vehicle; if the first to-be-scheduled orders in the to-be-scheduled order set meet the combination rule, judging whether the combined first to-be-scheduled orders with the same departure place address and the same destination address in the to-be-scheduled order set exceed the bearing upper limit of the bearing vehicle type; if yes, not merging the first order to be scheduled in the order set to be scheduled; if not, combining the first orders to be scheduled with the same starting place address and the same destination address to obtain a second order to be scheduled.

Optionally, in a third implementation manner of the first aspect of the present invention, the performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route includes: establishing a corresponding multidimensional vector according to the order information of the second order to be dispatched, and inputting the multidimensional vector into a preset greedy algorithm to obtain an initial route set; carrying out route destruction reconstruction processing on the initial route set to obtain a better route set; and inputting the preferred route set into a preset objective function to obtain the optimal route meeting the requirements of the objective function, and taking the optimal route as a delivery route.

Optionally, in a fourth implementation manner of the first aspect of the present invention, the performing a route destruction reconstruction process on the initial route set to obtain a better route set includes: selecting one or more initial routes from the initial route set, and removing all second orders to be scheduled in the initial routes; randomly inserting the removed second order to be scheduled into other routes to obtain a current round of better set; and optimizing the local optimal set by using a simulated annealing algorithm to obtain a local optimal route set, iterating for N times until N meets a preset value, and outputting to obtain a optimal route set.

Optionally, in a fifth implementation manner of the first aspect of the present invention, the calculating, according to the delivery route and a preset cost algorithm, a delivery route cost for each vehicle to be scheduled to deliver the second order to be scheduled includes: determining the number of signing addresses on a distribution route according to order information of a second order to be scheduled on the same distribution route, and calculating a handover fee according to the number of the signing addresses; calculating a first distance between each vehicle to be dispatched and the initial position of the delivery route; calculating the mileage charge of each vehicle to be dispatched according to the first distance, the second distance of the distribution route and the preset unit distance distribution cost; and acquiring preset starting fees and loading and unloading fees, and calculating the distribution route cost of each vehicle to be dispatched for distributing the second order to be dispatched according to the starting fees, the loading and unloading fees, the handover fees and the mileage fees.

Optionally, in a sixth implementation manner of the first aspect of the present invention, the selecting, according to the delivery route cost and preset constraint conditions, a vehicle to be scheduled from the set of vehicles to be scheduled as a delivery vehicle for delivering the second order to be scheduled includes: screening vehicles to be dispatched which accord with the constraint conditions from the vehicle to be dispatched in a centralized manner; and selecting the vehicle to be dispatched with the lowest delivery route cost from the vehicles to be dispatched which meet the constraint condition as the delivery vehicle for delivering the second order to be dispatched.

A second aspect of the present invention provides an order scheduling apparatus, including: the acquisition module is used for acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled; the judging module is used for judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information; the splitting and combining module is used for splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to a splitting rule or a combining rule when the first order to be scheduled in the order set to be scheduled meets one of the preset splitting rule or the preset combining rule; the path planning module is used for planning a path according to the order information of the second order to be scheduled to obtain at least one delivery route; the cost calculation module is used for sorting the second order to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second order to be scheduled according to the distribution route and a preset cost algorithm; and the screening module is used for screening the vehicles to be scheduled from the vehicles to be scheduled in a centralized manner as the delivery vehicles for delivering the second order to be scheduled according to the delivery route cost and preset constraint conditions.

Optionally, in a first implementation manner of the second aspect of the present invention, the order information at least includes a departure location address, a destination address, a cargo size, a cargo quantity, and a type of a loaded vehicle, and the determining module is specifically configured to: judging whether the first order to be scheduled exceeds the bearing upper limit of the bearing vehicle type according to the cargo size and the cargo quantity of the first order to be scheduled; if so, the first order to be scheduled conforms to the splitting rule; if not, judging whether a first order to be scheduled with the same departure place address and the same destination address exists in the order set to be scheduled; and if so, the first order to be scheduled accords with the merging rule.

Optionally, in a second implementation manner of the second aspect of the present invention, the splitting and merging module is specifically configured to: if a first order to be scheduled in the order set to be scheduled meets the splitting rule, splitting the first order to be scheduled into at least two second orders to be scheduled according to the quantity of the goods, wherein the second order to be scheduled is smaller than the bearing upper limit of the type of the borne vehicle; if the first to-be-scheduled orders in the to-be-scheduled order set meet the combination rule, judging whether the combined first to-be-scheduled orders with the same departure place address and the same destination address in the to-be-scheduled order set exceed the bearing upper limit of the bearing vehicle type; if yes, not merging the first order to be scheduled in the order set to be scheduled; if not, combining the first orders to be scheduled with the same starting place address and the same destination address to obtain a second order to be scheduled.

Optionally, in a third implementation manner of the second aspect of the present invention, the path planning module includes: the vector establishing unit is used for establishing a corresponding multi-dimensional vector according to the order information of the second order to be dispatched, and inputting the multi-dimensional vector into a preset greedy algorithm to obtain an initial route set; the destroying reconstruction unit is used for carrying out destroying reconstruction processing on the initial route set to obtain a better route set; and the function calculation unit is used for inputting the preferred route set into a preset target function to obtain the optimal route meeting the requirement of the target function, and taking the optimal route as a distribution route.

Optionally, in a fourth implementation manner of the second aspect of the present invention, the destroy reconstruction unit is specifically configured to: selecting one or more initial routes from the initial route set, and removing all second orders to be scheduled in the initial routes; randomly inserting the removed second order to be scheduled into other routes to obtain a current round of better set; and optimizing the local optimal set by using a simulated annealing algorithm to obtain a local optimal route set, iterating for N times until N meets a preset value, and outputting to obtain a optimal route set.

Optionally, in a fifth implementation manner of the second aspect of the present invention, the cost calculating module is specifically configured to: determining the number of signing addresses on a distribution route according to order information of a second order to be scheduled on the same distribution route, and calculating a handover fee according to the number of the signing addresses; calculating a first distance between each vehicle to be dispatched and the initial position of the delivery route; calculating the mileage charge of each vehicle to be dispatched according to the first distance, the second distance of the distribution route and the preset unit distance distribution cost; and acquiring preset starting fees and loading and unloading fees, and calculating the distribution route cost of each vehicle to be dispatched for distributing the second order to be dispatched according to the starting fees, the loading and unloading fees, the handover fees and the mileage fees.

Optionally, in a sixth implementation manner of the second aspect of the present invention, the screening module is specifically configured to: screening vehicles to be dispatched which accord with the constraint conditions from the vehicle to be dispatched in a centralized manner; and selecting the vehicle to be dispatched with the lowest delivery route cost from the vehicles to be dispatched which meet the constraint condition as the delivery vehicle for delivering the second order to be dispatched.

A third aspect of the present invention provides an order scheduling apparatus, comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line; the at least one processor invokes the instructions in the memory to cause the order scheduling apparatus to perform the steps of the order scheduling method described above.

A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to perform the steps of the above-described order scheduling method.

According to the technical scheme, order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled are obtained; judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information; if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to the splitting rule or the combining rule; performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route; sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm; and according to the distribution route cost and preset constraint conditions, intensively screening the vehicles to be dispatched from the vehicles to be dispatched as distribution vehicles for distributing the second orders to be dispatched. According to the scheme, the orders are reasonably split and combined, the logistics cost is saved, meanwhile, the constraint condition is added to the scheduling algorithm, the optimal logistics scheduling scheme can be obtained according to the scheduling requirement, and the logistics cost is further saved.

Drawings

Fig. 1 is a schematic diagram of a first embodiment of an order scheduling method according to an embodiment of the present invention;

FIG. 2 is a diagram illustrating a second embodiment of an order scheduling method according to an embodiment of the present invention;

fig. 3 is a schematic diagram of a third embodiment of an order scheduling method according to an embodiment of the present invention;

fig. 4 is a schematic diagram of a fourth embodiment of an order scheduling method according to the embodiment of the present invention;

fig. 5 is a schematic diagram of a fifth embodiment of an order scheduling method according to the embodiment of the present invention;

fig. 6 is a schematic diagram of an embodiment of an order scheduling apparatus according to an embodiment of the present invention;

fig. 7 is a schematic diagram of another embodiment of an order scheduling apparatus according to an embodiment of the present invention;

FIG. 8 is a diagram illustrating an embodiment of an order scheduling apparatus according to an embodiment of the present invention;

Detailed Description

The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

For convenience of understanding, a specific flow of the embodiment of the present invention is described below, and referring to fig. 1, a first embodiment of an order scheduling method according to the embodiment of the present invention includes:

101. acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

it is to be understood that the executing agent of the present invention may be an order scheduling apparatus, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.

In this embodiment, the data of the order may include all information related to the order, for example, information such as a departure address, a destination address, a vehicle type of a carrier, a cargo size, and a cargo quantity corresponding to the order, where the vehicle information of the current vehicle set to be scheduled mainly includes a vehicle capable of performing vehicle scheduling when logistics scheduling is currently required, the vehicle information mainly includes location information of the vehicle, a vehicle type, and the like, and the system is capable of acquiring information such as a load bearing weight of the vehicle according to the vehicle type.

102. Judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combination rules or not according to the order information;

103. if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to a splitting rule or a combining rule;

in practical applications, the order submitted by the user is not physically an inseparable unit, that is: the method is not an entity with the minimum granularity, can be used for decomposing in various forms, can also be used for combining orders according to conditions, and can be used for decomposing in different forms according to different service scenes. The corresponding rule setting is carried out according to different reasons that orders need to be split or combined, and the first reason that a self-built warehouse exists for some large-scale e-commerce companies, commodities can be prepared in different warehouses according to the previous shipment data, if the orders of users comprise commodities in a plurality of warehouses, then different warehouse commodities need to be split, the splitting rule is to inquire the stock quantity of the commodities corresponding to the orders in the self-built warehouse of the e-commerce company, if the quantity of the commodities corresponding to the orders in the nearest self-built warehouse is insufficient, the orders are split, the commodities are taken from another self-built warehouse, the second reason and the orders of the users are settled across shops, at this time, the splitting rule needs to split the orders according to the merchants corresponding to the commodities in the orders, the third reason corresponds to the cross-border commodities, and the third reason needs to carry out order and payment, and each order can not exceed 2000 yuan, year can not 2 ten thousand yuan, if the amount of a single order of a user exceeds 2000 yuan, the order must be split, each split sub-order can not exceed 2000 yuan, and each sub-order has an independent order number and a logistics order number respectively, so that normal clearance is ensured, the splitting rule carries out order splitting according to the amount of cross-border commodities, because four, different logistics companies have special requirements on the weight or volume of a single package, for example, some logistics companies stipulate that the single package can not exceed 20kg, and a situation also exists: a 10kg package may be charged higher than two 5kg packages, and an order is typically split into two based on logistics cost considerations, with splitting rules splitting the order according to logistics company regulations or cost considerations. The merging reasons of the orders are relatively simple, mainly cost is considered, under the condition that the starting address and the destination address of the orders are the same corresponding to the same e-commerce and the same customer, in order to save cost, the two orders are merged and delivered, and meanwhile, the weight and the quantity of the goods merged by the two orders do not exceed the preset bearing upper limit of the bearing vehicle.

104. Performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route;

in this embodiment, route planning is mainly performed based on a greedy algorithm and an adaptive large neighborhood algorithm, initial route planning is performed through the greedy algorithm, paths from a distribution center to destination addresses of all orders to be scheduled are mainly updated through a constructed adjacency matrix, then the shortest distances from the distribution center to the other destination addresses are continuously updated by means of the other destination addresses, and a better distribution route is calculated through the adaptive large neighborhood algorithm.

105. Sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm;

in this embodiment, after a plurality of delivery routes are generated in route planning, each delivery route corresponds to an order to be scheduled to be delivered, order information of the order to be scheduled of the same delivery route is summarized, delivery route costs of the delivery routes planned by delivery routes of all vehicles to be scheduled in a vehicle set to be scheduled are respectively calculated, and the delivery route costs are used as one of bases for selecting vehicles to be scheduled in the next step.

106. And according to the cost of the delivery route and preset constraint conditions, intensively screening the vehicles to be scheduled from the vehicles to be scheduled as delivery vehicles for delivering the second orders to be scheduled.

In the embodiment, a plurality of constraint conditions are set, for example, the service time of the vehicle, which is the time required for the delivery route to be delivered, cannot exceed the service time limit of the vehicle; the vehicle needs to pick up goods after the earliest picking time of the order, and the order is not considered when the order has no picking time; the vehicle needs to arrive before the latest delivery time of the order, and the order is not considered if the order is not delivered; the distribution distance traveled by the vehicle cannot exceed the mileage limit of the vehicle; loading orders by vehicles, wherein the maximum load and the maximum load capacity cannot be exceeded; road traffic control time, road traffic control vehicles; and later considered. The usable vehicles of the same type can be multiple, and the usable vehicles cannot exceed a given vehicle; and (4) the order needs to be completely loaded, unless the vehicles are not enough, and the like, if the vehicles to be dispatched which meet the preset conditions are more than one, the vehicle to be dispatched, of which the delivery route cost is the lowest, is selected as the dispatching vehicle.

In the embodiment, order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled are obtained; judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information; if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to the splitting rule or the combining rule; performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route; sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm; and according to the distribution route cost and preset constraint conditions, intensively screening the vehicles to be dispatched from the vehicles to be dispatched as distribution vehicles for distributing the second orders to be dispatched. According to the scheme, the orders are reasonably split and combined, the logistics cost is saved, meanwhile, the constraint condition is added to the scheduling algorithm, the optimal logistics scheduling scheme can be obtained according to the scheduling requirement, and the logistics cost is further saved.

Referring to fig. 2, a second embodiment of the order scheduling method according to the embodiment of the present invention includes:

201. acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

step 201 in this embodiment is similar to step 101 in the first embodiment, and is not described here again.

202. Judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combination rules or not according to the order information;

in practical applications, the order submitted by the user is not physically an inseparable unit, that is: the method is not an entity with the minimum granularity, can be used for decomposing in various forms, can also be used for combining orders according to conditions, and can be used for decomposing in different forms according to different service scenes. According to different reasons that orders need to be split or combined, corresponding rule setting is carried out, in the embodiment, whether the order to be scheduled can be completed by a carrying vehicle or not is considered, a default vehicle type for carrying the order can be set in order information, when the quantity and the weight of goods in the order exceed the upper limit of the volume and the weight which can be carried by the carrying vehicle, the order splitting needs to be carried out, so that the goods can be carried by the carrying vehicle, the splitting can be carried out in a mode that the goods are equally split, the number and the weight of the equally split goods are calculated, if the quantity and the weight of the goods still exceed the upper limit of the carrying capacity, the equally splitting continues until the split goods can be carried by the carrying vehicle, and the split goods form a new order.

203. If so, the first order to be scheduled conforms to the splitting rule;

204. splitting the first order to be scheduled into at least two second orders to be scheduled according to the quantity of goods, wherein the second orders to be scheduled are smaller than the bearing upper limit of the type of the bearing vehicle;

205. if not, judging whether a first order to be scheduled with the same departure place address and the same destination address exists in the order set to be scheduled;

206. if yes, the first order to be scheduled accords with the merging rule;

207. judging whether the combined first orders to be scheduled with the same departure place address and the same destination address in the order set to be scheduled exceed the bearing upper limit of the type of the borne vehicle or not;

208. if the order number exceeds the upper limit, the first orders to be scheduled in the order set to be scheduled are not merged;

209. if the starting address does not exceed the upper limit, combining the first orders to be scheduled with the same starting address and the same destination address to obtain a second order to be scheduled;

in this embodiment, the merging reasons of the orders are relatively simple, mainly cost consideration is given, in order to save cost, two orders are merged and delivered under the condition that the starting address and the destination address of the orders are the same for the same e-commerce and the same customer, meanwhile, the weight and the quantity of the goods after merging the two orders do not exceed the preset bearing upper limit of the bearing vehicle, the merging rule firstly detects the orders with the same starting address and destination address in the order set, and calculates whether the quantity and the weight of the goods of the merged orders are greater than the bearing weight of the vehicle, and for the merged orders greater than the bearing weight of the vehicle, merging is cancelled.

210. Performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route;

211. sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm;

212. and according to the cost of the delivery route and preset constraint conditions, intensively screening the vehicles to be scheduled from the vehicles to be scheduled as delivery vehicles for delivering the second orders to be scheduled.

The

steps

210 and 212 in the present embodiment are similar to the

steps

104 and 106 in the first embodiment, and are not described herein again.

On the basis of the previous embodiment, the embodiment describes in detail the process of splitting and combining the orders to be scheduled to form a new order, and splits the orders to be scheduled, which have a heavy cargo weight, according to the preset splitting rule, so as to ensure that the load-bearing vehicle can bear the cargo of the order, and simultaneously combines the orders with the same address information according to the preset combining rule, so that the logistics transportation cost can be saved.

Referring to fig. 3, a third embodiment of the order scheduling method according to the present invention includes:

301. acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

302. judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combination rules or not according to the order information;

303. if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to a splitting rule or a combining rule;

the steps 301-303 in the present embodiment are similar to the steps 101-103 in the first embodiment, and are not described herein again.

304. Establishing a corresponding multi-dimensional vector according to order information of a second order to be dispatched, and inputting the multi-dimensional vector into a preset greedy algorithm to obtain an initial route set;

in this embodiment, the multidimensional vector comprises an address flow direction and a time window, wherein the address flow direction is the starting address and the ending address of the order to be scheduled, and the time window is the customer delivery time and the required delivery time.

In practical applications, the greedy algorithm means that the choice that seems best at the present time is always made when solving the problem. That is, not considering the overall optimization, the method only makes a local optimal solution in a certain sense, and by inputting the multidimensional vector into a preset greedy algorithm formula, a path with the minimum distance from a certain point to the next node and the minimum time consumption is calculated, and all paths are combined to obtain an initial route set.

305. Selecting one or more initial routes from the initial route set, and removing all second orders to be scheduled in the initial routes;

306. randomly inserting the removed second order to be scheduled into other routes to obtain a current round of better set;

in this embodiment, the order to be scheduled of the selected initial route is randomly removed, the removed order to be scheduled is randomly inserted into other routes, the route with the minimum distance and the minimum consumed time is calculated, and the position where the order to be scheduled is inserted into other routes is determined, so that a better set of the current round is obtained.

307. Optimizing the current round of better set by using a simulated annealing algorithm to obtain a current round of optimal route set, iterating for N times until N meets a preset value, and outputting to obtain a better route set;

308. inputting the preferred route set into a preset objective function to obtain an excellent route meeting the requirements of the objective function, and taking the excellent route as a delivery route;

in practical application, in simulated annealing, the temperature change is that the initial high temperature is more than or equal to the temperature slowly reduced more than or equal to the end of the low temperature. The temperature level determines the likelihood of accepting a new solution to prevent the predicament of falling into a locally optimal solution. The simulated annealing algorithm starts from a certain high initial temperature, and randomly searches a global optimal solution of the objective function in a solution space by combining with the probability jump characteristic along with the continuous decrease of the temperature parameter, namely, the global optimal solution can jump out probabilistically in a local optimal solution and finally tends to be global optimal. The probability of accepting poor solutions is guaranteed to be 50% by the initial high temperature, the temperature is gradually reduced in the model iteration process, after a certain condition is met (such as after 5000 rounds of iteration), the temperature can be reduced to a certain value, the probability of accepting poor solutions is zero at this time, global convergence is achieved, and therefore the optimal route of the current round of iteration is obtained.

309. Sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm;

310. and according to the cost of the delivery route and preset constraint conditions, intensively screening the vehicles to be scheduled from the vehicles to be scheduled as delivery vehicles for delivering the second orders to be scheduled.

Steps 309-310 in this embodiment are similar to steps 105-106 in the first embodiment, and are not described herein again.

On the basis of the previous embodiment, the process of performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route is described in detail, a corresponding multidimensional vector is established according to the order information of the second order to be scheduled, and the multidimensional vector is input into a preset greedy algorithm to obtain an initial route set; carrying out route destruction reconstruction processing on the initial route set to obtain a better route set; and inputting the preferred route set into a preset objective function to obtain the optimal route meeting the requirements of the objective function, and taking the optimal route as a distribution route. The method can be used in a plurality of ways.

Referring to fig. 4, a fourth embodiment of the order scheduling method according to the embodiment of the present invention includes:

401. acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

402. judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combination rules or not according to the order information;

403. if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to a splitting rule or a combining rule;

404. performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route;

the

steps

401 and 404 in this embodiment are similar to the

steps

101 and 104 in the first embodiment, and are not described herein again.

405. Sorting second orders to be scheduled corresponding to the order information according to the same distribution route principle according to the distribution route, determining the number of signing addresses on the distribution route according to the order information of the second orders to be scheduled on the same distribution route, and calculating the handover fee according to the number of the signing addresses;

406. calculating a first distance between each vehicle to be dispatched and the initial position of the distribution route; .

In the embodiment, the distance is calculated mainly through vehicle position information in the vehicle information of the vehicle to be dispatched, wherein the vehicle position information is mainly sent to a dispatching center through a gprs or 3g wireless communication network by a gps positioning terminal device installed on the vehicle, and the dispatching center calculates the distance value between two places according to the vehicle position and the starting position of the delivery route.

407. Calculating mileage charge of each vehicle to be dispatched according to the first distance, the second distance of the distribution route and the preset unit distance distribution cost;

408. acquiring preset starting fees and loading and unloading fees, and calculating the distribution route cost of each vehicle to be dispatched for distributing the second order to be dispatched according to the starting fees, the loading and unloading fees, the handover fees and the mileage fees;

in the present embodiment, the handling fee is a reward to the cargo handling service by a person, a machine, or the like in the transportation route of the cargo, the starting fee and the handling fee are set after being summarized based on historical experience, and the delivery fee is mainly paid several times depending on the number of times of the order receipt address in the distribution route.

409. And according to the cost of the delivery route and preset constraint conditions, intensively screening the vehicles to be scheduled from the vehicles to be scheduled as delivery vehicles for delivering the second orders to be scheduled.

Step 409 in this embodiment is similar to step 106 in the first embodiment, and is not described here again.

On the basis of the previous embodiment, the embodiment describes in detail the process of calculating the cost of each vehicle to be scheduled for delivering the delivery route of the second order to be scheduled according to the delivery route and a preset cost algorithm, determines the number of the signing addresses on the delivery route according to the order information of the second order to be scheduled on the same delivery route, and calculates the hand-over fee according to the number of the signing addresses; calculating a first distance between each vehicle to be dispatched and the initial position of the distribution route; calculating mileage charge of each vehicle to be dispatched according to the first distance, the second distance of the distribution route and the preset unit distance distribution cost; and acquiring preset starting fees and loading and unloading fees, and calculating the distribution route cost of each vehicle to be dispatched for distributing the second order to be dispatched according to the starting fees, the loading and unloading fees, the handover fees and the mileage fees. The calculation of the distribution route cost is realized by respectively calculating the starting cost, the loading and unloading cost, the handover cost and the mileage cost, and the calculation is further used for determining the vehicle to be dispatched.

Referring to fig. 5, a fifth embodiment of the order scheduling method according to the present invention includes:

501. acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

502. judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combination rules or not according to the order information;

503. if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to a splitting rule or a combining rule;

504. performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route;

505. sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm;

the steps 501-505 in the present embodiment are similar to the steps 101-105 in the first embodiment, and are not described herein again.

506. Screening vehicles to be dispatched which accord with constraint conditions from the vehicles to be dispatched in a centralized manner;

in the embodiment, a plurality of constraint conditions are set, for example, the service time of the vehicle, which is the time required for the delivery route to be delivered, cannot exceed the service time limit of the vehicle; the vehicle needs to pick up goods after the earliest picking time of the order, and the order is not considered when the order has no picking time; the vehicle needs to arrive before the latest delivery time of the order, and the order is not considered if the order is not delivered; the distribution distance traveled by the vehicle cannot exceed the mileage limit of the vehicle; loading orders by vehicles, wherein the maximum load and the maximum load capacity cannot be exceeded; road traffic control time, road traffic control vehicles; and later considered. The usable vehicles of the same type can be multiple, and the usable vehicles cannot exceed a given vehicle; the order needs to be fully loaded unless the vehicle is not sufficient, etc.

507. And selecting the vehicle to be dispatched with the lowest delivery route cost from the vehicles to be dispatched which meet the constraint condition as a delivery vehicle for delivering the second order to be dispatched.

In this embodiment, if the number of vehicles to be dispatched, which meet the preset condition, is greater than one, the vehicle to be dispatched, which has the lowest cost of the delivery route, is selected as the dispatching vehicle.

On the basis of the foregoing embodiment, the present embodiment describes in detail a process of selecting vehicles to be scheduled from the vehicles to be scheduled collectively as delivery vehicles for delivering the second order to be scheduled according to the delivery route cost and preset constraint conditions, and collectively screens the vehicles to be scheduled that meet the constraint conditions from the vehicles to be scheduled; and selecting the vehicle to be dispatched with the lowest delivery route cost from the vehicles to be dispatched which accord with the constraint condition as a delivery vehicle for delivering the second order to be dispatched, and obtaining an optimal logistics dispatching scheme by adding the constraint condition, thereby saving the logistics cost.

The order scheduling method provided in the embodiment of the present invention is described above, and an order scheduling apparatus in the embodiment of the present invention is described below, referring to fig. 6, where an embodiment of the order scheduling apparatus in the embodiment of the present invention includes:

the acquiring module 601 is configured to acquire order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

a determining module 602, configured to determine, according to the order information, whether a first order to be scheduled in the order set to be scheduled meets one of a preset splitting rule or a preset combining rule;

a splitting and merging module 603, configured to split or merge a first to-be-scheduled order in the to-be-scheduled order set into a second to-be-scheduled order according to a splitting rule or a merging rule when the first to-be-scheduled order in the to-be-scheduled order set meets one of the preset splitting rule and the preset merging rule;

a path planning module 604, configured to perform path planning according to the order information of the second order to be scheduled, so as to obtain at least one delivery route;

the cost calculation module 605 is configured to sort, according to the distribution route, the second to-be-scheduled orders corresponding to the order information according to the same distribution route principle, and calculate, according to the distribution route and a preset cost algorithm, a distribution route cost for each to-be-scheduled vehicle to distribute the second to-be-scheduled orders;

and a screening module 606, configured to screen vehicles to be scheduled from the vehicle set to be scheduled as delivery vehicles for delivering the second order to be scheduled according to the delivery route cost and preset constraint conditions.

In the embodiment of the invention, the order scheduling device runs the order scheduling method, and the device acquires the order information of the order set to be scheduled and the vehicle information of the current vehicle set to be scheduled; judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information; if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to the splitting rule or the combining rule; performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route; sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm; and according to the distribution route cost and preset constraint conditions, intensively screening the vehicles to be dispatched from the vehicles to be dispatched as distribution vehicles for distributing the second orders to be dispatched. According to the scheme, the orders are reasonably split and combined, the logistics cost is saved, meanwhile, the constraint condition is added to the scheduling algorithm, the optimal logistics scheduling scheme can be obtained according to the scheduling requirement, and the logistics cost is further saved.

Referring to fig. 7, a second embodiment of the order scheduling apparatus according to the present invention includes:

Optionally, the order information at least includes a departure location address, a destination address, a cargo size, a cargo quantity, and a type of a loaded vehicle, and the determining module 602 is specifically configured to: judging whether the first order to be scheduled exceeds the bearing upper limit of the bearing vehicle type according to the cargo size and the cargo quantity of the first order to be scheduled; if so, the first order to be scheduled conforms to the splitting rule; if not, judging whether a first order to be scheduled with the same departure place address and the same destination address exists in the order set to be scheduled; and if so, the first order to be scheduled accords with the merging rule.

Optionally, the splitting and merging module 603 is specifically configured to: if a first order to be scheduled in the order set to be scheduled meets the splitting rule, splitting the first order to be scheduled into at least two second orders to be scheduled according to the quantity of the goods, wherein the second order to be scheduled is smaller than the bearing upper limit of the type of the borne vehicle; if the first to-be-scheduled orders in the to-be-scheduled order set meet the combination rule, judging whether the combined first to-be-scheduled orders with the same departure place address and the same destination address in the to-be-scheduled order set exceed the bearing upper limit of the bearing vehicle type; if yes, not merging the first order to be scheduled in the order set to be scheduled; if not, combining the first orders to be scheduled with the same starting place address and the same destination address to obtain a second order to be scheduled.

Wherein the path planning module 604 comprises: a vector establishing unit 6041, configured to establish a corresponding multidimensional vector according to the order information of the second order to be scheduled, and input the multidimensional vector into a preset greedy algorithm to obtain an initial route set; a destroy reconstruction unit 6042, configured to perform destroy reconstruction processing on the initial route set to obtain a better route set; and a function calculation unit 6043, configured to input the better route set into a preset objective function, to obtain an excellent route meeting the requirement of the objective function, and use the excellent route as a distribution route.

Optionally, the destroy reconstruction unit 6042 is specifically configured to: selecting one or more initial routes from the initial route set, and removing all second orders to be scheduled in the initial routes; randomly inserting the removed second order to be scheduled into other routes to obtain a current round of better set; and inputting the optimal set of the current round into a simulated annealing algorithm to obtain an optimal route set of the current round, and iterating the optimal route set to preset times to obtain an optimal route set.

Optionally, the cost calculating module 605 is specifically configured to: determining the number of signing addresses on a distribution route according to order information of a second order to be scheduled on the same distribution route, and calculating a handover fee according to the number of the signing addresses; calculating a first distance between each vehicle to be dispatched and the initial position of the delivery route; calculating the mileage charge of each vehicle to be dispatched according to the first distance, the second distance of the distribution route and the preset unit distance distribution cost; and acquiring preset starting fees and loading and unloading fees, and calculating the distribution route cost of each vehicle to be dispatched for distributing the second order to be dispatched according to the starting fees, the loading and unloading fees, the handover fees and the mileage fees.

Optionally, the screening module 606 is specifically configured to: screening vehicles to be dispatched which accord with the constraint conditions from the vehicle to be dispatched in a centralized manner; and selecting the vehicle to be dispatched with the lowest delivery route cost from the vehicles to be dispatched which meet the constraint condition as the delivery vehicle for delivering the second order to be dispatched.

On the basis of the previous embodiment, the unit structures of the functional modules are added, through the unit structures, the logistics cost is saved by reasonably splitting and combining orders, and meanwhile, by adding constraint conditions to the scheduling algorithm, the optimal logistics scheduling scheme can be obtained according to the scheduling requirement, and the logistics cost is further saved.

Fig. 6 and fig. 7 describe the order scheduling apparatus in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the order scheduling device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

Fig. 8 is a schematic structural diagram of an order scheduling apparatus 800 according to an embodiment of the present invention, where the order scheduling apparatus 800 may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 810 (e.g., one or more processors) and a memory 820, and one or more storage media 830 (e.g., one or more mass storage devices) storing an application 833 or data 832. Memory 820 and storage medium 830 may be, among other things, transient or persistent storage. The program stored in the storage medium 830 may include one or more modules (not shown), each of which may include a series of instruction operations for the order scheduling apparatus 800. Further, the processor 810 may be configured to communicate with the storage medium 830, and execute a series of instruction operations in the storage medium 830 on the order scheduling apparatus 800 to implement the steps of the order scheduling method described above.

The order scheduling apparatus 800 may also include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input-output interfaces 860, and/or one or more operating systems 831, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will appreciate that the configuration of the order scheduling facility shown in FIG. 8 does not constitute a limitation of the order scheduling facility provided herein, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.

The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, which may also be a volatile computer readable storage medium, having stored therein instructions, which, when executed on a computer, cause the computer to perform the steps of the order scheduling method.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses, and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. An order scheduling method, characterized in that the order scheduling method comprises:

acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information;

if so, splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to the splitting rule or the combining rule;

performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route;

sorting second orders to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second orders to be scheduled according to the distribution route and a preset cost algorithm;

and according to the distribution route cost and preset constraint conditions, intensively screening the vehicles to be dispatched from the vehicles to be dispatched as distribution vehicles for distributing the second orders to be dispatched.

2. The order scheduling method according to claim 1, wherein the order information at least includes a departure address, a destination address, a cargo size, a cargo quantity, and a type of a loaded vehicle, and the determining whether a first to-be-scheduled order in the to-be-scheduled order set conforms to one of preset splitting rules or merging rules according to the order information includes:

judging whether the first order to be scheduled exceeds the bearing upper limit of the bearing vehicle type according to the cargo size and the cargo quantity of the first order to be scheduled;

if so, the first order to be scheduled conforms to the splitting rule;

if not, judging whether a first order to be scheduled with the same departure place address and the same destination address exists in the order set to be scheduled;

and if so, the first order to be scheduled accords with the merging rule.

3. The order scheduling method according to claim 2, wherein the splitting or merging the first to-be-scheduled order in the to-be-scheduled order set into the second to-be-scheduled order according to the splitting rule or the merging rule comprises:

if a first order to be scheduled in the order set to be scheduled meets the splitting rule, splitting the first order to be scheduled into at least two second orders to be scheduled according to the quantity of the goods, wherein the second order to be scheduled is smaller than the bearing upper limit of the type of the borne vehicle;

if the first to-be-scheduled orders in the to-be-scheduled order set meet the combination rule, judging whether the combined first to-be-scheduled orders with the same departure place address and the same destination address in the to-be-scheduled order set exceed the bearing upper limit of the bearing vehicle type;

if yes, not merging the first order to be scheduled in the order set to be scheduled;

if not, combining the first orders to be scheduled with the same starting place address and the same destination address to obtain a second order to be scheduled.

4. The order scheduling method according to claim 1, wherein the performing path planning according to the order information of the second order to be scheduled to obtain at least one delivery route comprises:

establishing a corresponding multidimensional vector according to the order information of the second order to be dispatched, and inputting the multidimensional vector into a preset greedy algorithm to obtain an initial route set;

carrying out route destruction reconstruction processing on the initial route set to obtain a better route set;

and inputting the preferred route set into a preset objective function to obtain the optimal route meeting the requirements of the objective function, and taking the optimal route as a delivery route.

5. The order scheduling method according to claim 4, wherein the performing of route destruction reconstruction processing on the initial route set to obtain a better route set comprises:

selecting one or more initial routes from the initial route set, and removing all second orders to be scheduled in the initial routes;

randomly inserting the removed second order to be scheduled into other routes to obtain a current round of better set;

and optimizing the local optimal set by using a simulated annealing algorithm to obtain a local optimal route set, iterating for N times until N meets a preset value, and outputting a optimal route set.

6. The order scheduling method according to any one of claims 1 to 5, wherein the calculating a delivery route cost for each vehicle to be scheduled to deliver the second order to be scheduled according to the delivery route and a preset cost algorithm comprises:

determining the number of signing addresses on a distribution route according to order information of a second order to be scheduled on the same distribution route, and calculating a handover fee according to the number of the signing addresses;

calculating a first distance between each vehicle to be dispatched and the initial position of the delivery route;

calculating the mileage charge of each vehicle to be dispatched according to the first distance, the second distance of the distribution route and the preset unit distance distribution cost;

and acquiring preset starting fees and loading and unloading fees, and calculating the distribution route cost of each vehicle to be dispatched for distributing the second order to be dispatched according to the starting fees, the loading and unloading fees, the handover fees and the mileage fees.

7. The order scheduling method according to claim 6, wherein said selecting vehicles to be scheduled from said set of vehicles to be scheduled as delivery vehicles for delivering said second order to be scheduled according to said delivery route cost and preset constraints comprises:

screening vehicles to be dispatched which accord with the constraint conditions from the vehicle to be dispatched in a centralized manner;

and selecting the vehicle to be dispatched with the lowest delivery route cost from the vehicles to be dispatched which meet the constraint condition as the delivery vehicle for delivering the second order to be dispatched.

8. An order scheduling apparatus, comprising:

the acquisition module is used for acquiring order information of an order set to be scheduled and vehicle information of a current vehicle set to be scheduled;

the judging module is used for judging whether a first order to be scheduled in the order set to be scheduled meets one of preset splitting rules or combining rules or not according to the order information;

the splitting and combining module is used for splitting or combining a first order to be scheduled in the order set to be scheduled into a second order to be scheduled according to a splitting rule or a combining rule when the first order to be scheduled in the order set to be scheduled meets one of the preset splitting rule or the preset combining rule;

the path planning module is used for planning a path according to the order information of the second order to be scheduled to obtain at least one delivery route;

the cost calculation module is used for sorting the second order to be scheduled corresponding to the order information according to the distribution route and the same distribution route principle, and calculating the distribution route cost of each vehicle to be scheduled for distributing the second order to be scheduled according to the distribution route and a preset cost algorithm;

and the screening module is used for screening the vehicles to be scheduled from the vehicles to be scheduled in a centralized manner as the delivery vehicles for delivering the second order to be scheduled according to the delivery route cost and preset constraint conditions.

9. An order scheduling apparatus, characterized by comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;

the at least one processor invoking the instructions in the memory to cause the order scheduling apparatus to perform the steps of the order scheduling method of any of claims 1-7.

10. A computer-readable storage medium, having a computer program stored thereon, wherein the computer program, when being executed by a processor, is adapted to carry out the steps of the order scheduling method according to any of the claims 1-7.