Solving capacitated vehicle routing problems using edge histogram based sampling algorithms

Author

Tsutsui, Shigeyoshi ; Wilson, Gordon

Author_Institution

Dept. of Manage. Inf., Hannan Univ., Osaka, Japan

Volume

1

fYear

2004

fDate

19-23 June 2004

Firstpage

1150

Abstract

In evolutionary algorithms based on probabilistic modeling, the offspring population is generated according to the estimated probability density model of the parent instead of using recombination and mutation operators. In previous papers, we have proposed an edge histogram based sampling algorithm (EHBSA) based on probabilistic model-building genetic algorithms (PMBGAs) and showed they work well on sequencing problems; the TSP and flow shop scheduling problems. In this paper, we apply EHBSA for solving capacitated vehicle routing problems (CVRP). The results showed EHBSA work fairly well on the CVRP and it also worked better than well-known traditional two-parent recombination operators.

Keywords

flow shop scheduling; genetic algorithms; probability; sampling methods; transportation; travelling salesman problems; TSP; capacitated vehicle routing problems; edge histogram based sampling algorithms; evolutionary algorithm; flow shop scheduling; mutation operator; offspring population; probabilistic model-building genetic algorithm; probabilistic modeling; probability density model; sequencing problems; traveling salesman problem; two-parent recombination operator; Evolutionary computation; Genetic algorithms; Genetic mutations; Histograms; Information management; Job shop scheduling; Routing; Sampling methods; Symmetric matrices; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2004. CEC2004. Congress on

Print_ISBN

0-7803-8515-2

Type

conf

DOI

10.1109/CEC.2004.1330991

Filename

1330991