Crossover and Diversity : A Study about GVR

Genetic Vehicle Representation (GVR) is a two level representational scheme, designed to deal in an effective way with all the information needed by candidate solutions, for the Vehicle Routing Problem (VRP). In this paper, we present an analysis on the influence of two crossover operators in the algorithm performance. A first study on diversity is also presented, regarding the issues of diversity measurement and possible relations to the algorithm performance. Results show that for GVR one type of crossover is more suited for solving VRP instances, and both operators may not avoid the loss of diversity. Nevertheless, solutions discovered by GVR are competitive and are the best ones found by an evolutionary algorithm.

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

[2]  Graham Kendall,et al.  Advanced Population Diversity Measures in Genetic Programming , 2002, PPSN.

[3]  Penousal Machado,et al.  On the influence of GVR in vehicle routing , 2003, SAC '03.

[4]  Loo Hay Lee,et al.  Hybrid Genetic Algorithm in Solving Vehicle Routing Problems with Time Window Constraints (APORS) , 2000 .

[5]  Sam R. Thangiah,et al.  Vehicle Routing with Time Windows using Genetic Algorithms , 1997 .

[6]  Graham Kendall,et al.  A Survey And Analysis Of Diversity Measures In Genetic Programming , 2002, GECCO.

[7]  Sushil J. Louis,et al.  Syntactic Analysis of Convergence in Genetic Algorithms , 1992, FOGA.

[8]  Penousal Machado,et al.  Vehicle Routing Problem: Doing It The Evolutionary Way , 2002, GECCO.

[9]  Jean-François Cordeau,et al.  VRP with Time Windows , 1999, The Vehicle Routing Problem.

[10]  Penousal Machado,et al.  GVR DELIVERS IT ON TIME , 2002 .

[11]  Jacques Desrosiers,et al.  2-Path Cuts for the Vehicle Routing Problem with Time Windows , 1997, Transp. Sci..

[12]  Jean Berger,et al.  A Hybrid Genetic Algorithm for the Vehicle Routing Problem with Time Windows , 1998, Canadian Conference on AI.

[13]  Olli Bräysy.  Efficient Local Search Algorithms for the Vehicle Routing Problem with Time Windows , 2001 .

[14]  Penousal Machado,et al.  GVR: A New Genetic Representation for the Vehicle Routing Problem , 2002, AICS.

[15]  Russell Bent,et al.  A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows , 2004, Transp. Sci..