Paper Info
Title
Target aiming Pareto search and its application to the vehicle routing problem with route balancing
Abstract
In this paper, we present a solution method for a bi-objective vehicle routing problem, called the vehicle routing problem with route balancing (VRPRB), in which the total length and balance of the route lengths are the objectives under consideration. The method, called Target Aiming Pareto Search, is defined to hybridize a multi-objective genetic algorithm for the VRPRB using local searches. The method is based on repeated local searches with their own appropriate goals. We also propose an implementation of the Target Aiming Pareto Search using tabu searches, which are efficient meta-heuristics for the vehicle routing problem. Assessments with standard metrics on classical benchmarks demonstrate the importance of hybridization as well as the efficiency of the Target Aiming Pareto Search.
Year
DOI
Venue
2007
10.1007/s10732-007-9022-6
J. Heuristics
Keywords
Field
DocType
Routing,Multi-objective optimization,Tabu search,Hybrid algorithm
Vehicle routing problem,Mathematical optimization,Hybrid algorithm,Guided Local Search,Destination-Sequenced Distance Vector routing,Multi-objective optimization,Artificial intelligence,Pareto principle,Machine learning,Tabu search,Genetic algorithm,Mathematics
Journal
Volume
Issue
ISSN
13
5
1381-1231
Citations 
PageRank 
References 
22
1.07
13
Authors
3
Name
Order
Citations
PageRank
Nicolas Jozefowiez134821.58
Frédéric Semet2129996.47
El-Ghazali Talbi32186179.85