A genetic algorithm for subset sum problem

被引：18

作者：

Wang, RL ^{[1
]}

机构：

[1] Univ Fukui, Fac Engn, Fukui 9108507, Japan

来源：

NEUROCOMPUTING | 2004年 / 57卷

关键词：

genetic algorithm; crossover; mutation; subset sum problem;

D O I：

10.1016/j.neucom.2003.12.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an improved genetic algorithm (GA) for solving the subset sum problem (SSP). Unlike a conventional GA, the proposed algorithm performs conditional (and not probable) crossover and mutation. Simulation results show that the proposed GA is capable of finding an optimal solution for the SSP. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：463 / 468

页数：6

共 10 条

[1]

[Anonymous], 1989, GENETIC ALGORITHM SE

[2]

[Anonymous], 1979, Computers and Intractablity: A Guide to the Theoryof NP-Completeness

[3] A design optimization tool based on a genetic algorithm [J].