Target aiming Pareto search and its application to the vehicle routing problem with route balancing

被引:53
|
作者
Jozefowiez, Nicolas [1 ]
Semet, Frederic
Talbi, El-Ghazali
机构
[1] Univ Sci & Tech Lille, Lab Informat Fondamentale Lille, Villeneuve Dascq, France
[2] Univ Valenciennes Hainaut Cambresis, Lab Automat Mec Informat Ind Humaines, Valence, France
关键词
routing; multi-objective; optimization; tabu search; hybrid algorithm;
D O I
10.1007/s10732-007-9022-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:455 / 469
页数:15
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