MACS-VRPTW

MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows. MACS-VRPTW, an Ant Colony Optimization based approach useful to solve vehicle routing problems with time windows is presented. MACS-VRPTW is organized with a hierarchy of artificial ant colonies designed to successively optimize a multiple objective function: the first colony minimizes the number of vehicles while the second colony minimizes the traveled distances. Cooperation between colonies is performed by exchanging information through pheromone updating. We show that MACS-VRPTW is competitive with the best known existing methods both in terms of solution quality and computation time. Moreover, MACS-VRPTW improves some of the best solutions known for a number of problem instances in the literature. 2 Chapter 5 MACS-VRPTW: A MULTIPLE ANT COLONY SYSTEM FOR VEHICLE ROUTING PROBLEMS WITH TIME WINDOWS 5.1. Introduction This chapter presents MACS-VRPTW, a Multiple Ant Colony System for Vehicle Routing Problems with Time Windows. MACS-VRPTW is based on Ant Colony System (ACS) (Gambard.


References in zbMATH (referenced in 83 articles )

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  1. Ehrgott, Matthias; Gandibleux, Xavier: Hybrid metaheuristics for multi-objective combinatorial optimization (2008) ioport
  2. Hu, Xiao-Min; Zhang, Jun; Li, Yun: Orthogonal methods based ant colony search for solving continuous optimization problems (2008) ioport
  3. Kong, Min; Tian, Peng; Kao, Yucheng: A new ant colony optimization algorithm for the multidimensional Knapsack problem (2008)
  4. Socha, Krzysztof; Dorigo, Marco: Ant colony optimization for continuous domains (2008)
  5. Solnon, Christine: Combining two pheromone structures for solving the car sequencing problem with ant colony optimization (2008)
  6. Cheng, Chi-Bin; Mao, Chun-Pin: A modified ant colony system for solving the travelling salesman problem with time windows (2007)
  7. Ellabib, Issmail; Calamai, Paul; Basir, Otman: Exchange strategies for multiple Ant Colony System (2007) ioport
  8. García-Martínez, C.; Cordón, O.; Herrera, F.: A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP (2007)
  9. Liao, Ching-Jong; Juan, Hsiao-Chien: An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups (2007)
  10. Lim, Andrew; Zhang, Xingwen: A two-stage heuristic with ejection pools and generalized ejection chains for the vehicle routing problem with time windows (2007)
  11. Alba, Enrique; Dorronsoro, Bernabé: Computing nine new best-so-far solutions for capacitated VRP with a cellular genetic algorithm (2006)
  12. Chabrier, Alain: Vehicle routing problem with elementary shortest path based column generation (2006)
  13. Ghoseiri, Keivan; Morshedsolouk, Fahimeh: ACS-TS: Train scheduling using ant colony system (2006)
  14. Ombuki, Beatrice; Ross, Brian J.; Hanshar, Franklin: Multi-objective genetic algorithms for vehicle routing problem with time windows (2006) ioport
  15. Reimann, Marc; Ulrich, Heinz: Comparing backhauling strategies in vehicle routing using ant colony optimization (2006)
  16. Sitarz, Sebastian: Hybrid methods in multi-criteria dynamic programming (2006)
  17. Solnon, Christine; Fenet, Serge: A study of ACO capabilities for solving the maximum clique problem (2006)
  18. Tan, K. C.; Chew, Y. H.; Lee, L. H.: A hybrid multi-objective evolutionary algorithm for solving truck and trailer vehicle routing problems (2006)
  19. Boryczka, Mariusz: Eliminating introns in ant colony programming (2005)
  20. Dorigo, Marco; Blum, Christian: Ant colony optimization theory: a survey (2005)