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MAX-MIN Ant system

Authors:

Thomas Stützle,

Holger H. HoosAuthors Info & Claims

Future Generation Computer Systems, Volume 16, Issue 9

Pages 889 - 914

Published: 01 June 2000 Publication History

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Wu DYang QZhou CZheng ZZhang JLi XHandl J(2024)Adapted Ant Colony Optimization for Large-Scale Orienteering ProblemProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3638530.3654270(223-226)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638530.3654270
Dinot MDoerr BHennebelle UWill SElkind E(2023)Runtime analyses of multi-objective evolutionary algorithms in the presence of noiseProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/616(5549-5557)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/616
Liu YQiu JHart EYu YGan ZLi WSilva SPaquete L(2023)Learning-Based Neural Ant Colony OptimizationProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590483(47-55)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590483
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MAX-MIN Ant system

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In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stochastically generates its candidate solution, in a given iteration, based on the same pheromone and heuristic information as every other ant. Stubborn ...

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cover image Future Generation Computer Systems

Future Generation Computer Systems Volume 16, Issue 9

June 2000

94 pages

ISSN:0167-739X

Editor:
L. O. Hertzberger
Univ. of Amsterdam, Amsterdam, Netherlands

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 June 2000

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Wu DYang QZhou CZheng ZZhang JLi XHandl J(2024)Adapted Ant Colony Optimization for Large-Scale Orienteering ProblemProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3638530.3654270(223-226)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638530.3654270
Dinot MDoerr BHennebelle UWill SElkind E(2023)Runtime analyses of multi-objective evolutionary algorithms in the presence of noiseProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/616(5549-5557)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/616
Liu YQiu JHart EYu YGan ZLi WSilva SPaquete L(2023)Learning-Based Neural Ant Colony OptimizationProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590483(47-55)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590483
Assimi HKoch BGarcia CWagner MNeumann FHong JBures MPark JCerny T(2022)Run-of-mine stockyard recovery scheduling and optimisation for multiple reclaimersProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing10.1145/3477314.3507130(1074-1083)Online publication date: 25-Apr-2022
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Zelinka IDas S(2022)Gamesourcing: an unconventional tool to assist the solution of the traveling salesman problemNatural Computing: an international journal10.1007/s11047-020-09817-z21:2(347-357)Online publication date: 1-Jun-2022
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Popović EIvković NČrepinšek M(2022)ACOCaRS: Ant Colony Optimization Algorithm for Traveling Car Renter ProblemBioinspired Optimization Methods and Their Applications10.1007/978-3-031-21094-5_3(31-45)Online publication date: 17-Nov-2022
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Pascariu BSamà MPellegrini PD’Ariano ARodriguez JPacciarelli D(2022)Performance Evaluation of a Parallel Ant Colony Optimization for the Real-Time Train Routing Selection Problem in Large InstancesEvolutionary Computation in Combinatorial Optimization10.1007/978-3-031-04148-8_4(46-61)Online publication date: 20-Apr-2022
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Čechová PKubala M(2021)Comparison of three nature inspired molecular docking algorithmsInternational Journal of Bio-Inspired Computation10.1504/ijbic.2021.11336217:1(34-41)Online publication date: 1-Jan-2021
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Nurcahyadi TBlum C(2021)Negative Learning in Ant Colony Optimization: Application to the Multi Dimensional Knapsack ProblemProceedings of the 2021 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence10.1145/3461598.3461602(22-27)Online publication date: 10-Apr-2021
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Benbaki RBenomar ZDoerr BKrawiec K(2021)A rigorous runtime analysis of the 2-MMASib on jump functionsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3449639.3459350(4-13)Online publication date: 26-Jun-2021
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Optimization of the quadratic assignment problem using an ant colony algorithm

A new hybrid method based on Particle Swarm Optimization, Ant Colony Optimization and 3-Opt algorithms for Traveling Salesman Problem

Improving the performance of MAX-MIN ant system on the TSP using stubborn ants

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