CN115081995A - Vehicle scheduling method and device for cold-chain logistics and electronic equipment - Google Patents
Vehicle scheduling method and device for cold-chain logistics and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application provides a vehicle scheduling method, a vehicle scheduling device and electronic equipment for cold-chain logistics, wherein the method comprises the following steps: acquiring the optimal storage time and the maximum storage space; selecting a store with the shortest travel time away from the distribution center from all stores as a current store, placing the current store into a target store set, and recording first travel time and first required goods quantity; updating the store with the shortest travel time from the current store to the current store, and recording the second travel time and the second quantity of required goods; after updating the current store, judging whether the accumulated running time exceeds the optimal storage time, if so, not adding the current store into the target store set, if not, judging whether the accumulated storage quantity exceeds the maximum storage quantity, if so, not adding the current store into the target store set, and if not, adding the current store into the target store set; and scheduling the corresponding vehicle according to the target store set.
Description
Technical Field
The present disclosure relates to the field of semiconductor storage, and in particular, to a vehicle scheduling method and apparatus for cold-chain logistics, and an electronic device.
Background
With the rapid development of socioeconomic performance in China, cold-chain logistics also meet new development opportunities. The scale of the cold-chain logistics industry is enlarged year by year, the facilities and equipment in the industry are continuously improved, and professional talents in the industry are also continuously emerged.
In the cold chain transportation process, the condition that the transport vehicle is unloaded for many times in the midway may exist, and the continuous change of the temperature and the humidity of the peripheral environment of the vehicle may cause the deterioration and the damage of goods in the vehicle. The existing vehicle for cold chain transportation is difficult to take the temperature change into consideration when planning the path.
Disclosure of Invention
In view of the above, there is a need to provide a vehicle scheduling method and apparatus for cold-chain logistics, and an electronic device, which can implement reasonable planning of a delivery route of a vehicle.
A first aspect of the present application provides a vehicle scheduling method for cold-chain logistics, for scheduling vehicles, the vehicle scheduling method including:
step a, obtaining the optimal storage time of the vehicle and the maximum storage space of the vehicle;
b, selecting the store with the shortest travel time from the distribution center from all stores as a current store, putting the current store into a target store set corresponding to the vehicle, and recording a first travel time from the distribution center to the current store and a first required goods quantity of the current store;
step c, updating the store which has the shortest travel time from the current store to other stores not belonging to the target store set as the current store, and recording a second travel time from the current store before updating to the current store after updating and a second demand quantity of the current store after updating;
step d of, after updating the current store, determining whether an accumulated travel time exceeds the optimal storage time, where the accumulated travel time is a sum of the first travel time and the second travel time, if the accumulated travel time exceeds the optimal storage time, not placing the updated current store into the target store set, and if the accumulated travel time does not exceed the optimal storage time, executing step e;
step e, determining whether the accumulated storage capacity exceeds a maximum storage capacity, where the accumulated storage capacity is a sum of the first demand capacity and the second demand capacity, if the accumulated storage capacity exceeds the maximum storage capacity, not placing the updated current store into the target store set, and if the accumulated storage capacity does not exceed the maximum storage capacity, placing the updated current store into the target store set and repeatedly executing step c; and
and f, scheduling the corresponding vehicle according to the target store set.
With reference to the first aspect of the present application, in a more possible implementation manner, the vehicle scheduling method further includes: regulating temperature according to carriage
And calculating a first temperature coefficient according to the parameters of the compartment temperature zone
Wherein the compartment temperature zone parameter comprises a first upper limit temperature
And a first lower limit temperature
， 
(ii) a Regulating temperature according to carriage
And calculating a second temperature coefficient according to the temperature requirement parameter of the goods
Wherein the cargo temperature requirement parameter comprises a second upper limit temperature
Second lower limit temperature
， 
(ii) a And storing the time according to the reference
First ratio coefficient
Second proportionality coefficient
The third ratio
The first temperature coefficient
And the second temperature coefficient
Obtaining the optimal storage time
Wherein
， 
。
with reference to the first aspect of the present application, in a more possible implementation manner, before step a, the vehicle scheduling method further includes: acquiring first preset running time between each store and a distribution center and second preset running time between each store and other stores; and acquiring the preset demand quantity of each store, wherein the preset demand quantity comprises the first demand quantity and the second demand quantity.
With reference to the first aspect of the present application, in a more possible implementation manner, the vehicle scheduling method further includes: and after the accumulated travel time exceeds the optimal storage time or the accumulated storage capacity exceeds the maximum storage capacity, repeating the steps a to e, and adding the remaining stores which do not belong to the target store set corresponding to other vehicles until all stores are put into the target store set.
With reference to the first aspect of the present application, in a more possible implementation manner, the vehicle scheduling method further includes: after each time a new store is added to the target store set, the accumulated travel time is increased by a preset discharge time.
A second aspect of the present application provides a vehicle scheduling apparatus for cold-chain logistics, for scheduling a vehicle, the vehicle scheduling apparatus comprising: the first acquisition module is used for acquiring the optimal storage time of the vehicle and the maximum storage space of the vehicle;
the first selection module is used for selecting the store which has the shortest travel time from the distribution center from all stores as a current store, and placing the current store into a target store set corresponding to the vehicle;
the first recording module is used for recording a first driving time from the distribution center to the current store and a first demand quantity of the current store;
the second selection module is used for updating the store which has the shortest travel time from the current store to the current store in other stores which do not belong to the target store set;
the second recording module is used for recording a second driving time from the current store before updating to the current store after updating and a second demand quantity of the current store after updating;
a first judging module, configured to judge whether an accumulated travel time exceeds the optimal storage time after updating the current store, where the accumulated travel time is a sum of the first travel time and the second travel time, and if the accumulated travel time exceeds the optimal storage time, not to place the updated current store into the target store set;
a second determination module, configured to determine whether an accumulated stored cargo amount exceeds the maximum stored cargo amount when the accumulated travel time does not exceed the optimal storage time, where the accumulated stored cargo amount is a sum of the first required cargo amount and the second required cargo amount, if the accumulated stored cargo amount exceeds the maximum stored cargo amount, the updated current store is not placed in the target store set, and if the accumulated stored cargo amount does not exceed the maximum stored cargo amount, the updated current store is placed in the target store set; and
and the execution module is used for scheduling the corresponding vehicle according to the target store set.
With reference to the second aspect of the present application, in a more possible implementation manner, the vehicle scheduling apparatus further includes: a first calculation module for adjusting temperature according to the carriage
And calculating a first temperature coefficient by using the parameters of the temperature zone of the carriage
Wherein the compartment temperature zone parameter comprises a first upper limit temperature
And a first lower limit temperature
， 
(ii) a A second calculation module for adjusting temperature according to the carriage
And calculating a second temperature coefficient according to the temperature requirement parameter of the goods
Wherein the cargo temperature requirement parameter comprises a second upper limit temperature
Second lower limit temperature
， 
(ii) a A third calculation module for storing time according to the reference
First ratio coefficient
Second proportionality coefficient
The third ratio
The first temperature coefficient
And the second temperature coefficient
Obtaining the optimal storage time
Wherein
， 
。
with reference to the second aspect of the present application, in a more possible implementation manner, the vehicle scheduling apparatus further includes: the second acquisition module is used for acquiring first preset driving time between each store and the distribution center and second preset driving time between each store and other stores; and the third acquisition module is used for acquiring the preset demand quantity of each store, wherein the preset demand quantity comprises the first demand quantity and the second demand quantity.
A third aspect of the present application provides an electronic device, which includes a controller and a memory, where the memory is used to store a plurality of program instructions, and when the controller calls the program instructions, the vehicle scheduling method for cold-chain logistics as described above is implemented.
Compared with the prior art, the application has at least the following beneficial effects:
based on the first constraint rule, namely whether the accumulated running time exceeds the optimal storage time or not, and the second constraint rule, namely whether the accumulated storage cargo volume exceeds the maximum storage cargo volume or not, and sequentially selecting close stores for distribution, the reasonable planning of the distribution path of the vehicle for cold-chain logistics can be realized.
Drawings
Fig. 1 is a schematic flow chart of a vehicle scheduling method for cold-chain logistics according to an embodiment of the present application.
Fig. 2 is a sub-flowchart of step S13 in fig. 1.
Fig. 3 is a schematic diagram of a vehicle dispatching device for cold-chain logistics in an embodiment of the application.
Fig. 4 is a schematic diagram of an electronic device according to an embodiment of the present application.
The following detailed description will further illustrate the present application in conjunction with the above-described figures.
Description of the main elements
100. A vehicle dispatching device for cold chain logistics; 10. a first acquisition module; 21. a first selection module; 22. a first recording module; 31. a second selection module; 32. a second recording module; 40. a first judgment module; 50. a second judgment module; 60. an execution module; 71. a first calculation module; 72. a second calculation module; 73. a third calculation module; 80. a second acquisition module; 90. a third obtaining module; 200. an electronic device; 210. a memory; 211. a computer program; 220. a processor.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof which are illustrated in the appended drawings. In addition, the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, and the embodiments described are merely some, but not all embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
Referring to fig. 1, an embodiment of the present application provides a vehicle dispatching method for cold-chain logistics, including the following steps:
in step S11, a first preset travel time between each store and the distribution center and a second preset travel time between each store and another store are obtained.
In one possible implementation, the first preset travel time and the second preset travel time can be obtained by calculating a travel distance between stores and a distribution center, a travel distance between each store, and an average travel speed of the vehicle.
It will be appreciated that vehicles used for cold chain transportation are typically fixed in a range of areas for the transportation of goods. At least one distribution center is arranged in the area, and the vehicle can drive to each store in the area for distribution after being loaded at the distribution center.
Step S12, obtaining the preset demand quantity of each store.
It will be appreciated that stores will have a certain amount of demand each time an order is placed. In one possible implementation, when an order is placed in a store, the order information directly provides the preset demand quantity.
In step S13, the optimal storage time of the vehicle and the maximum storage space of the vehicle are acquired.
It can be understood that since the vehicles for short-haul cold chain transportation need to be directly delivered in a plurality of stores, they need to be frequently unloaded and loaded for a while, and the external ambient temperature change may cause some damage to the goods stored in the vehicles that are not delivered yet. Therefore, the optimal storage time is provided for different goods, and the distribution of the goods in the optimal storage time can reduce the possibility of goods damage to the maximum extent.
In step S14, the store that has traveled the shortest time from the distribution center is selected from all stores as the current store, and the current store is placed in the target store group corresponding to the vehicle.
In one possible implementation, each vehicle determines a target store set before departure, and the vehicles sequentially go to stores in the target store set during transportation to deliver goods.
It will be appreciated that the location of the various stores to be reached needs to be predetermined before the vehicle can be transported.
In one possible implementation, the store with the shortest travel time from the distribution center is taken as the first store to be distributed in the target store set by comparing the travel time between all stores and the distribution center. It can be understood that the preference is selected closely store and is carried out the delivery and be favorable to guaranteeing the integrity of goods, avoids the vehicle to cause the damage of goods in the car after the goods are unloaded to many times loading.
It is to be understood that the current store is the store that is making the distance traveled determination to determine whether to join the target set of stores.
And step S15, recording a first driving time from the distribution center to the current store and a first demand quantity of the current store.
In this embodiment, the first travel time is a first preset travel time from the distribution center to a first distribution store, and the first demand amount is a preset demand amount of the store first distributed by the distribution center.
In step S16, the store that has the shortest travel time from the current store among the other stores not belonging to the target store set is updated as the current store.
In this embodiment, after the first store delivered by the delivery center has been determined, the store closest to the first store needs to be selected again among the remaining stores for delivery.
And step S17, recording a second driving time from the current store before updating to the current store after updating and a second demand quantity of the current store after updating.
In this embodiment, the second travel time is a second preset travel time from any one store (i.e., the current store before the update) to the next store (i.e., the current store after the update), and the second demand amount is a preset demand amount corresponding to the next store.
In step S18, after the current store is updated, it is determined whether or not the cumulative travel time exceeds the optimum storage time. Wherein the accumulated travel time is a sum of the first travel time and the second travel time. Step S191 is performed if the integrated travel time exceeds the optimum storage time, and step S19 is performed if the integrated travel time does not exceed the optimum storage time.
Further, in some embodiments, the accumulated travel time is increased by a preset discharge time each time a new store is added to the target store set. In these embodiments, the accumulated travel time is included as a sum of the first travel time, the second travel time, and the total dump time. In one possible implementation, the total drop time is a preset drop time multiplied by the number of stores in the target set of stores.
Step S19, it is determined whether the accumulated storage capacity exceeds the maximum storage capacity. The accumulated storage capacity is the sum of the first demand capacity and the second demand capacity, and if the accumulated storage capacity exceeds the maximum storage capacity, step S191 is performed. If the accumulated storage capacity does not exceed the maximum storage capacity, step S192 is performed.
In step S191, the updated current store is not added to the target store set.
It is understood that when the accumulated travel time exceeds the optimal storage time, the distribution of the updated store may affect the quality of the goods, and thus the updated store is not included in the target store set.
It will be appreciated that the vehicle is also not able to make deliveries to the store if the cumulative storage volume would exceed the maximum storage volume of the vehicle.
In step S192, the updated current store is added to the target store set, and step S16 is repeatedly performed.
It is understood that the step S16 is repeatedly executed to add more self-vehicles to the target store set to perform the distribution store.
It is understood that if the determination of the updated store is made after the vehicle is transported to one store (i.e., the first store in the target store set), and if the cumulative travel time exceeds the optimal storage time or the cumulative storage amount exceeds the maximum storage amount of the vehicle, the vehicle only delivers one store, that is, only one store in the target store set corresponding to the vehicle.
And step 20, scheduling the corresponding vehicle according to the target store set.
It is understood that the target store set corresponding to the vehicle can be obtained through steps S11 through S19. The vehicles can distribute goods in sequence according to the target store set, namely according to the sequence of joining targets with the set.
Obviously, the reasonable planning of the distribution route of the vehicle can be realized by the application based on the first constraint rule, namely whether the accumulated running time exceeds the optimal storage time or not, and the second constraint rule, namely whether the accumulated storage cargo quantity exceeds the maximum storage cargo quantity or not, and sequentially selecting close stores for distribution.
Please refer to fig. 2, which illustrates a sub-flowchart of step S13.
Step S131, a first temperature coefficient is calculated according to the compartment regulation temperature and compartment temperature zone parameters, wherein the compartment temperature zone parameters comprise a first upper limit temperature and a first lower limit temperature.
In one possible implementation, the first temperature coefficient
Can be obtained by the following formula (1):
Wherein,
the temperature of the carriage is adjusted,
in order to obtain the first temperature coefficient,
is a first upper limit temperature,
Is a first lower limit temperature. In a possible implementation manner, the first upper limit temperature and the first lower limit temperature respectively correspond to an upper limit value and a lower limit value of the storage temperature which can be provided by the vehicle, namely, any temperature value between the first upper limit temperature and the first lower limit temperature which can be provided by the vehicle for the cargo. For example, the first upper temperature limit is 10 ℃ and the first lower temperature limit is-20 ℃. It will be appreciated that the refrigerator consumes more energy as it provides a lower temperature, or a temperature closer to the first lower temperature limit.
It can be understood that each vehicle for cold chain transportation can utilize the refrigerating unit to refrigerate the carriage of refrigerator car or freezing car in certain extent to provide suitable storage environment for the goods, avoid leading to the damage of goods because of the change of external temperature, humidity.
Step S132, calculating a second temperature coefficient according to the regulated temperature of the carriage and the cargo temperature requirement parameters, wherein the cargo temperature requirement parameters comprise a second upper limit temperature and a second lower limit temperature.
In one possible implementation, the second temperature coefficient
Can be obtained by the following formula (2):
Wherein,
is the second upper limit temperature,
Is the second lower limit temperature. In one possible implementation manner, the second upper limit temperature and the second lower limit temperature respectively correspond to an upper limit value and a lower limit value of the storage temperature of the cargo demand. That is, the cargo can be stored in any temperature value between the second upper limit temperature and the second lower limit temperature along with the corresponding environment. It can be understood that, because the temperature in the vehicle changes along with the ambient temperature outside the vehicle in the running process of the vehicle, namely, the temperature in the vehicle can be regulated at the set temperature of the carriage
The vicinity fluctuates. When the carriage adjusts the temperature
Is close to the second lower limit temperature
Even if the temperature in the vehicle fluctuates, the storage of the goods cannot be influenced excessively. On the contrary, if the temperature of the carriage is adjusted
Is close to the second upper limit temperature
Once the temperature in the vehicle fluctuates, damage to the goods in the vehicle may be caused due to the high temperature. In other words, the temperature in the vehicle is higher than the second upper limit temperature
The influence is far more than that the temperature in the vehicle is lower than the second lower limit temperature
In (1).
Step S133, obtaining an optimal storage time according to the reference storage time, the first scaling factor, the second scaling factor, the third scaling factor, the first temperature factor, and the second temperature factor.
In one possible implementation, there is one reference storage time for each type of goods
. Reference storage time
The setting of (a) is generally dependent on the kind of goods, for example, whether it is refrigerated food, ice-temperature video, frozen food or ultra-low-temperature storage food. Storing the reference time
Multiplying a certain temperature coefficient to obtain the optimal storage time of the corresponding goods.
Further low, optimal storage time
Can be obtained by the following formula (3):
Wherein,
is a first scale factor and is a ratio of,
is a second scaling factor to be used for the second scaling factor,
is a third proportionality coefficient and satisfies
。
It can be understood thatA coefficient of proportionality
And the second proportionality coefficient
The value of (A) can reflect the corresponding temperature coefficient to the optimal storage time
The influence of (c). The size of the value can be obtained by the type of data retained during the dispatch that captures the history or by testing the data.
In one embodiment, the first scaling factor
=0.15, second proportionality coefficient
=0.15, third proportionality coefficient
=0.7。
In some embodiments, the vehicle scheduling method further comprises: after the accumulated travel time exceeds the optimal storage time in step S18 or the accumulated storage quantity exceeds the maximum storage quantity in step S19, steps 13 to 192 are repeatedly performed to join the remaining stores that do not belong to the target store group corresponding to another vehicle until all stores are placed in the corresponding target store group.
It is understood that by repeatedly performing the step S13 and the step S192, all the stores can be assigned to the delivery vehicle.
Referring to fig. 3, an embodiment of the present application provides a vehicle dispatching device 100 for cold-chain logistics, so as to dispatch vehicles. The vehicle dispatching device 100 for cold-chain logistics comprises a first obtaining module 10, a first selecting module 21, a first recording module 22, a second selecting module 31, a second recording module 32, a first judging module 40, a second judging module 50 and an executing module 60.
The first obtaining module 10 is used for obtaining the optimal storage time of the vehicle and the maximum storage space of the vehicle. Specifically, refer to step S13, which is not described herein again.
The first selecting module 21 is configured to select, from all stores, a store that has a shortest travel time from the distribution center as a current store, and place the current store into a target store set corresponding to the vehicle. Specifically, refer to step S14, which is not described herein again.
The first recording module 22 is used for recording a first driving time from the distribution center to the current store and a first demand quantity of the current store. Specifically, refer to step S15, which is not described herein again.
The second selecting module 31 is configured to update, as the current store, the store that has the shortest travel time from the current store among other stores that do not belong to the target store set. Specifically, refer to step S16, which is not described herein again.
The second recording module 32 is configured to record a second driving time from the current store before the update to the current store after the update, and a second quantity of the required goods of the current store after the update. Specifically, refer to step S17, which is not described herein again.
The first determining module 40 is configured to determine whether the accumulated travel time exceeds the optimal storage time after updating the current store, where the accumulated travel time is a sum of the first travel time and the second travel time, and if the accumulated travel time exceeds the optimal storage time, not add the updated current store to the target store set. Specifically, refer to step S18 and step S181, which are not described herein again.
The second determining module 50 is configured to determine whether the accumulated storage quantity exceeds the maximum storage quantity when the accumulated travel time does not exceed the optimal storage time, where the accumulated storage quantity is a sum of the first demand quantity and the second demand quantity, if the accumulated storage quantity exceeds the maximum storage quantity, the updated current store is not added to the target store set, and if the accumulated storage quantity does not exceed the maximum storage quantity, the updated current store is added to the target store set. Specifically, refer to step S19 and step S191, which are not described herein again.
The execution module 60 is configured to schedule the corresponding vehicle according to the set of target stores. Specifically, refer to step S20, which is not described herein again.
Further, the vehicle dispatching device 100 for cold-chain logistics further comprises: a first calculation module 71, a second calculation module 72 and a third calculation module 73.
The first calculating module 71 is configured to calculate a first temperature coefficient according to the compartment regulation temperature and the compartment temperature zone parameters, where the compartment temperature zone parameters include a first upper limit temperature and a first lower limit temperature. Specifically, refer to the step S131, which is not described herein again.
The second calculating module 72 is configured to calculate a second temperature coefficient according to the compartment adjustment temperature and the cargo temperature requirement parameter, where the cargo temperature requirement parameter includes a second upper limit temperature and a second lower limit temperature. Specifically, refer to the step S132, which is not described herein again.
The third calculating module 73 is configured to obtain an optimal storage time according to the reference storage time, the first scaling factor, the second scaling factor, the third scaling factor, the first temperature factor, and the second temperature factor. Specifically, refer to step S133, which is not described herein again.
Further, the vehicle dispatching device 100 for cold-chain logistics further comprises: a second acquisition module 80 and a third acquisition module 90.
The second obtaining module 80 is configured to obtain a first preset driving time between each store and the distribution center, and a second preset driving time between each store and other stores; and
the third obtaining module 90 is configured to obtain a preset demand quantity of each store, where the preset demand quantity includes the first demand quantity and the second demand quantity.
Referring to fig. 4, an electronic device 200 is also provided in the present embodiment. The electronic device 200 is applicable to vehicle scheduling.
The electronic device 200 comprises a memory 210, a processor 220 and a computer program 211 stored in the memory 210 and executable on the processor 220. The processor 220, when executing the computer program 211, implements the steps of the vehicle dispatching method for cold-chain logistics described above, such as steps S11-S20 shown in fig. 1 and steps S131-S133 shown in fig. 2. Alternatively, the processor 220, when executing the computer program 211, implements the functions of the modules/units in the embodiment of the vehicle dispatching device 100 for cold-chain logistics, such as the modules 10-90 in fig. 3.
Illustratively, the computer program 211 may be partitioned into one or more modules/units that are stored in the memory 210 and executed by the processor 220 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, the instruction segments describing the execution process of the computer program 211 in the electronic device 200. For example, the computer program 211 may be divided into a first obtaining module 10, a first selecting module 21, a first recording module 22, a second selecting module 31, a second recording module 32, a first judging module 40, a second judging module 50, an executing module 60, a first calculating module 71, a second calculating module 72, a third calculating module 73, a second obtaining module 80, and a third obtaining module 90 in fig. 3, where specific functions of the modules are described in the embodiment of the vehicle dispatching device 100 for cold-chain logistics.
Those skilled in the art will appreciate that the schematic diagram is merely an example of the electronic device 200, and does not constitute a limitation of the electronic device 200, and may include more or less components than those shown, or combine certain components, or different components, for example, the electronic device 200 may further include an input-output device, a network access device, a bus, etc.
The Processor 220 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor 220 may be any conventional processor or the like, the processor 220 being the control center of the electronic device 200 and connecting the various parts of the entire electronic device 200 using various interfaces and lines.
The memory 210 may be used for storing the computer program 211 and/or the module/unit, and the processor 220 implements various functions of the electronic device 200 by running or executing the computer program and/or the module/unit stored in the memory 210 and calling data stored in the memory 210. The memory 210 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phone book, etc.) created according to the use of the electronic apparatus 200, and the like. Further, the memory 210 may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
It is understood that the above-described embodiments of the electronic device are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice. In addition, each functional module in the embodiments of the present invention may be integrated into the same processing module, or each module may exist alone physically, or two or more modules may be integrated into the same module. The integrated module can be realized in a hardware form, and can also be realized in a form of hardware and a software functional module.
The embodiment of the application also provides a computer readable storage medium. The computer readable storage medium has stored therein program instructions, which when run on a computing device, cause the computing device to execute the vehicle scheduling method for cold-chain logistics provided by the foregoing embodiment.
The method and the device are based on the first constraint rule, namely whether the accumulated running time exceeds the optimal storage time or not, and the second constraint rule, namely whether the accumulated storage cargo quantity exceeds the maximum storage cargo quantity or not, and select close stores in sequence for distribution, so that reasonable planning of distribution paths of vehicles for cold-chain logistics can be realized.
It should be understood by those skilled in the art that the above embodiments are only for illustrating the present application and are not used as limitations of the present application, and that suitable modifications and changes of the above embodiments are within the scope of the claims of the present application as long as they are within the spirit and scope of the present application.
Claims (9)
1. A vehicle dispatching method for cold-chain logistics is used for dispatching vehicles, and is characterized in that the vehicle dispatching method comprises the following steps:
step a, obtaining the optimal storage time of the vehicle and the maximum storage space of the vehicle;
b, selecting the store with the shortest travel time from the distribution center from all stores as a current store, putting the current store into a target store set corresponding to the vehicle, and recording a first travel time from the distribution center to the current store and a first required goods quantity of the current store;
step c, updating the store which has the shortest travel time from the current store to other stores not belonging to the target store set as the current store, and recording a second travel time from the current store before updating to the current store after updating and a second demand quantity of the current store after updating;
step d, after updating the current store, judging whether the accumulated travel time exceeds the optimal storage time, wherein the accumulated travel time is the sum of the first travel time and the second travel time, if the accumulated travel time exceeds the optimal storage time, not putting the updated current store into the target store set, and if the accumulated travel time does not exceed the optimal storage time, executing step e;
step e, determining whether the accumulated storage capacity exceeds a maximum storage capacity, where the accumulated storage capacity is a sum of the first demand capacity and the second demand capacity, if the accumulated storage capacity exceeds the maximum storage capacity, not placing the updated current store into the target store set, and if the accumulated storage capacity does not exceed the maximum storage capacity, placing the updated current store into the target store set and repeatedly executing step c; and
and f, scheduling the corresponding vehicle according to the target store set.
2. The vehicle scheduling method of claim 1, further comprising:
regulating temperature according to carriage
And calculating a first temperature coefficient by using the parameters of the temperature zone of the carriage
Wherein the compartment temperature zone parameter comprises a first upper limit temperature
And a first lower limit temperature
，
；
Regulating temperature according to carriage
And calculating a second temperature coefficient according to the temperature requirement parameter of the goods
Wherein the cargo temperature requirement parameter comprises a second upper limit temperature
Second lower limit temperature
， 
(ii) a And
according to reference storage time
First ratio coefficient
Second proportionality coefficient
The third ratio
The first temperature coefficient
And the second temperature coefficient
Obtaining the optimal storage time
;
Wherein, 
， 
。
3. the vehicle dispatching method of claim 1, wherein prior to step a, the vehicle dispatching method further comprises:
acquiring first preset driving time between each store and a distribution center and second preset driving time between each store and other stores; and
and acquiring a preset demand quantity of each store, wherein the preset demand quantity comprises the first demand quantity and the second demand quantity.
4. The vehicle scheduling method of claim 1, further comprising: and after the accumulated travel time exceeds the optimal storage time or the accumulated storage capacity exceeds the maximum storage capacity, repeating the steps a to e, and adding the rest stores which do not belong to the target store set into the target store set corresponding to other vehicles until all stores are put into the target store set.
5. The vehicle scheduling method of claim 1, further comprising:
after each time a new store is added to the target store set, the accumulated travel time is increased by a preset discharge time.
6. A vehicle dispatching device for cold-chain logistics, used for dispatching vehicles, characterized in that the vehicle dispatching device comprises:
the first acquisition module is used for acquiring the optimal storage time of the vehicle and the maximum storage space of the vehicle;
the first selection module is used for selecting the store which has the shortest travel time from the distribution center from all stores as a current store, and placing the current store into a target store set corresponding to the vehicle;
the first recording module is used for recording a first driving time from the distribution center to the current store and a first demand quantity of the current store;
the second selection module is used for updating the store which has the shortest travel time from the current store to the current store in other stores which do not belong to the target store set;
the second recording module is used for recording a second driving time from the current store before updating to the current store after updating and a second demand quantity of the current store after updating;
a first judging module, configured to judge whether an accumulated travel time exceeds the optimal storage time after updating the current store, where the accumulated travel time is a sum of the first travel time and the second travel time, and if the accumulated travel time exceeds the optimal storage time, not to place the updated current store into the target store set;
a second determination module, configured to determine whether an accumulated stored cargo volume exceeds a maximum stored cargo volume when the accumulated travel time does not exceed the optimal storage time, where the accumulated stored cargo volume is a sum of the first required cargo volume and the second required cargo volume, if the accumulated stored cargo volume exceeds the maximum stored cargo volume, the updated current store is not placed in the target store set, and if the accumulated stored cargo volume does not exceed the maximum stored cargo volume, the updated current store is placed in the target store set; and
and the execution module is used for scheduling the corresponding vehicle according to the target store set.
7. The vehicle dispatching device of claim 6, further comprising:
a first calculation module for adjusting temperature according to the carriage
And calculating a first temperature coefficient according to the parameters of the compartment temperature zone
Wherein the compartment temperature zone parameter comprises a first upper limit temperature
And a first lower limit temperature
， 
；
A second calculation module for adjusting temperature according to the carriage
And calculating a second temperature coefficient according to the temperature requirement parameter of the goods
Wherein the cargo temperature requirement parameter comprises a second upper limit temperature
Second lower limit temperature
， 
；
Third computing ModuleFor storing time based on a reference
First ratio coefficient
Second proportionality coefficient
The third ratio
The first temperature coefficient
And the second temperature coefficient
Obtaining the optimal storage time
Wherein
， 
。
8. the vehicle dispatching device of claim 6, further comprising:
the second acquisition module is used for acquiring first preset driving time between each store and the distribution center and second preset driving time between each store and other stores; and
and the third acquisition module is used for acquiring the preset demand quantity of each store, wherein the preset demand quantity comprises the first demand quantity and the second demand quantity.
9. An electronic device, comprising a controller and a memory, wherein the memory is configured to store a plurality of program instructions, and wherein the controller, when invoked, implements a vehicle dispatch method as claimed in any one of claims 1 to 5.
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