Combining an evolutionary algorithm with data mining to solve a single-vehicle routing problem

被引：28
|
作者：
Santos, H. G. [1 ]
Ochi, L. S. [1 ]
Marinho, E. H. [1 ]
Drummond, L. M. A. [1 ]
机构：
[1] Univ Fed Fluminense, Dept Comp Sci, Niteroi, RJ, Brazil
来源：
NEUROCOMPUTING | 2006年 / 70卷 / 1-3期
关键词：
evolutionary algorithms; data mining; vehicle routing;
D O I：
10.1016/j.neucom.2006.07.008
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The aim of this work is to present some alternatives to improve the performance of an evolutionary algorithm applied to the problem known as the oil collecting vehicle routing problem. Some proposals based on the insertion of local search and data mining (DM) modules in a genetic algorithm (GA) are presented. Four algorithms were developed: a GA, a GA with a local search procedure, a GA including a DM module and a GA including local search and DM. Experimental results demonstrate that the incorporation of DM and local search modules in GA can improve the solution quality produced by this method. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码：70 / 77
页数：8
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