A parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet

Nowadays genetic algorithms stand as a trend to solve NPcomplete and NP-hard problems. In this paper, we present a new hybrid metaheuristic which uses Parallel Genetic Algorithms and Scatter Search coupled with a decomposition-into-petals procedure for solving a class of Vehicle Routing and Scheduli...

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Bibliographic Details
Published inLecture notes in computer science Vol. 1388; pp. 216 - 224
Main Authors Ochi, Luiz S., Vianna, Dalessandro S., Drummond, Lucia M. A., Victor, André O.
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 01.01.1998
Springer-Verlag
SeriesLecture Notes in Computer Science
Subjects
Exact sciences and technology
Genetic Algorithm
Information and communication sciences
Information science. Documentation
Library and information science. General aspects
Professional aspects
Scatter Search
Sciences and techniques of general use
Vehicle Route
Vehicle Route Problem
Vehicle Type
Parallel algorithm
Operations research
Genetic algorithm
Combinatorial problem
Vehicle routing problem
Search algorithm
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Summary:Nowadays genetic algorithms stand as a trend to solve NPcomplete and NP-hard problems. In this paper, we present a new hybrid metaheuristic which uses Parallel Genetic Algorithms and Scatter Search coupled with a decomposition-into-petals procedure for solving a class of Vehicle Routing and Scheduling Problems. The parallel genetic algorithm presented is based on the island model and was run on a cluster of workstations. Its performance is evaluated for a heterogeneous fleet problem, which is considered a problem much harder to solve than the homogeneous vehicle routing problem.
ISBN:3540643591
9783540643593
ISSN:0302-9743
1611-3349
DOI:10.1007/3-540-64359-1_691