Localized genetic algorithm for vehicle routing problem with time windows

Authors:
Ziauddin Ursani;Daryl Essam;David Cornforth;Robert Stocker
Affiliations:
UNSW@ADFA, ACT 2600, Australia;UNSW@ADFA, ACT 2600, Australia;Commonwealth Scientific and Industrial Research Organisation Steel River Estate, Mayfield West, NSW 2304, Australia;UNSW@ADFA, ACT 2600, Australia
Venue:
Applied Soft Computing
Year:
2011

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Abstract

This paper introduces the Localized Optimization Framework (LOF). This framework is an iterative procedure between two phases, Optimization and De-optimization. Optimization is done on the problem parts rather than the problem as a whole, while de-optimization is done on the whole problem. To test our hypothesis, we have chosen a genetic algorithm as an optimization methodology and Vehicle Routing Problem with Time Windows (VRPTW) as a domain space. We call this new scheme the Localized Genetic Algorithm (LGA). We demonstrate that the LGA is, on average, able to produce better solutions than most of the other heuristics on small scale problems of VRPTW. Furthermore the LGA has attained several new best solutions on popular datasets.