Application of improved Shuffle Frog Leaping Algorithm to resolve multi-objective optimization problem

Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (30): 233-238.

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Application of improved Shuffle Frog Leaping Algorithm to resolve multi-objective optimization problem

WANG Xiaodi1, XIAO Wei1, HE Can2

1.Hunan Normal University, Changsha 410081, China
2.Hunan CSONLINE Internet Transmission Co., Ltd, Changsha 410016, China

Online:2012-10-21 Published:2012-10-22

改进的蛙跳算法在多目标优化问题中的应用

王晓笛1，肖伟1，何灿2

1.湖南师范大学，长沙 410081
2.湖南星辰在线网络传播有限公司，长沙 410016

Abstract

Abstract: This paper draws genetic operators of GA and improves the method of SFLA group dividing based on introducing SFLA, puts forward an improved SFLA to resolve problem of multi-objective optimization. The improved method takes multi-objective 0-1 knapsack as an example for simulated experiment, which bears out that, compared with original SFLA, the improved SFLA has better performance on resolving improved SFLA problem.

Key words: Shuffle Frog Leaping Algorithm（SFLA）, multi-objective optimization, genetic operators, grouping method, multi-objective 0-1 knapsack problem

摘要： 在介绍原始混洗蛙跳算法的基础上，引入遗传算法中的遗传算子，改进原始蛙跳算法的分组方法，提出一种改进的混洗蛙跳算法用于求解多目标优化问题。改进的算法以多目标0-1背包问题为例进行模拟实验，其实验结果表示，与原始的混洗蛙跳算法相比较，改进的蛙跳算法在求解多目标优化问题上具有更好的性能。

关键词: 混洗蛙跳算法, 多目标优化问题, 遗传算子, 分组方法, 多目标0-1背包问题

WANG Xiaodi1, XIAO Wei1, HE Can2. Application of improved Shuffle Frog Leaping Algorithm to resolve multi-objective optimization problem[J]. Computer Engineering and Applications, 2012, 48(30): 233-238.

王晓笛1，肖伟1，何灿2. 改进的蛙跳算法在多目标优化问题中的应用[J]. 计算机工程与应用, 2012, 48(30): 233-238.

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Application of improved Shuffle Frog Leaping Algorithm to resolve multi-objective optimization problem

改进的蛙跳算法在多目标优化问题中的应用

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