A Hybrid Approach Based on Ant Colony System for the VRPTW

The main objective of vehicle routing problem (VRP) is to minimize the total required fleet size for serving all customers. Secondary objectives are to minimize the total distance traveled or to minimize the total route duration of all vehicles. In this paper, we present a hybrid ant colony System, named IACS, coupled with the iterated local search (ILS) algorithm for the VRP with time windows (VRPTW). The ILS can help to escape local optimum. Experiments on various aspects of the algorithm and computational results for some benchmark problems are reported. We compare our approach with some classic, powerful meta-heuristics and show that the proposed approach can obtain the better quality of the solutions.

[1]  F. Glover,et al.  Handbook of Metaheuristics , 2019, International Series in Operations Research & Management Science.

[2]  Paolo Toth,et al.  The Vehicle Routing Problem , 2002, SIAM monographs on discrete mathematics and applications.

[3]  Daniel Angus,et al.  Multiple objective ant colony optimisation , 2009, Swarm Intelligence.

[4]  Helena Ramalhinho Dias Lourenço,et al.  Iterated Local Search , 2001, Handbook of Metaheuristics.

[5]  R. Eberhart,et al.  Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[6]  Richard F. Hartl,et al.  Applying the ANT System to the Vehicle Routing Problem , 1999 .

[7]  Abraham P. Punnen,et al.  The traveling salesman problem and its variations , 2007 .

[8]  Aboul Ella Hassanien,et al.  Computational Intelligence in Biomedicine and Bioinformatics, Current Trends and Applications , 2008, Computational Intelligence in Biomedicine and Bioinformatics.

[9]  Yuanhai Li,et al.  Optimal groundwater monitoring design using an ant colony optimization paradigm , 2007, Environ. Model. Softw..

[10]  Roberto Montemanni,et al.  A new algorithm for a Dynamic Vehicle Routing Problem based on Ant Colony System , 2002 .

[11]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[12]  Angus R. Simpson,et al.  Ant Colony Optimization Applied to Water Distribution System Design: Comparative Study of Five Algorithms , 2007 .

[13]  Edward W. Felten,et al.  Large-Step Markov Chains for the Traveling Salesman Problem , 1991, Complex Syst..

[14]  Richard K. Moore,et al.  From theory to applications , 1986 .

[15]  William J. Cook,et al.  Combinatorial optimization , 1997 .

[16]  Luca Maria Gambardella,et al.  MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows , 1999 .

[17]  Silvano Martello,et al.  Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization , 2012 .

[18]  Jun Zhang,et al.  Flexible Protein Folding by Ant Colony Optimization , 2008, Computational Intelligence in Biomedicine and Bioinformatics.

[19]  Luca Maria Gambardella,et al.  Solving symmetric and asymmetric TSPs by ant colonies , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[20]  T. Stützle,et al.  MAX-MIN Ant System and local search for the traveling salesman problem , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[21]  Roberto Montemanni,et al.  Ant colony optimization for real-world vehicle routing problems , 2007, Swarm Intelligence.

[22]  David S. Johnson,et al.  Experimental Analysis of Heuristics for the STSP , 2007 .

[23]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..