Cellular artificial glowworm swarm optimization algorithm for multiple-choice knapsack problem

Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (14): 70-72.

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Cellular artificial glowworm swarm optimization algorithm for multiple-choice knapsack problem

CHENG Kui1, MA Liang1, LIU Yong1，2

1.College of Management, University of Shanghai for Science and Technology, Shanghai 200093, China
2.Foundation Courses Department, Yancheng Institute of Technology, Yancheng, Jiangsu 224051, China

Online:2013-07-15 Published:2013-07-31

多选择背包问题的元胞萤火虫算法

程魁1，马良1，刘勇1，2

1.上海理工大学管理学院，上海 200093
2.盐城工学院基础教学部，江苏盐城 224051

Abstract

Abstract: In order to solve the multiple-choice knapsack problem, based on the principles of cellular automata and artificial glowworm swarm optimization algorithm, this paper presents a novel cellular artificial glowworm swarm optimization algorithm for multiple-choice knapsack problem. Cellular and its neighbor are introduced into the algorithm to maintain the swarm’s diversity and the algorithm uses evolutionary rule of cellular in local optimization to avoid local optima. Simulated tests of multiple-choice knapsack problem and comparisons with other algorithms show the algorithm is feasible and effective and the algorithm has strong global optimization ability.

Key words: artificial glowworm swarm optimization algorithm, cellular automata, multiple-choice knapsack problem, optimization

摘要： 为有效求解多选择背包问题，基于元胞自动机的原理和萤火虫算法，提出一种求解多选择背包问题的元胞萤火虫算法。将元胞及其邻居引入到算法中来保持种群的多样性，利用元胞的演化规则进行局部优化，避免算法陷入局部极值。通过对典型多选择背包问题的仿真实验和其他算法的比较，表明该算法可行有效，有良好的全局优化能力。

关键词: 萤火虫算法, 元胞自动机, 多选择背包问题, 优化

CHENG Kui1, MA Liang1, LIU Yong1，2. Cellular artificial glowworm swarm optimization algorithm for multiple-choice knapsack problem[J]. Computer Engineering and Applications, 2013, 49(14): 70-72.

程魁1，马良1，刘勇1，2. 多选择背包问题的元胞萤火虫算法[J]. 计算机工程与应用, 2013, 49(14): 70-72.

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Cellular artificial glowworm swarm optimization algorithm for multiple-choice knapsack problem

多选择背包问题的元胞萤火虫算法

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