多选择背包问题的元胞萤火虫算法  

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

作　　者：程魁[1] 马良[1] 刘勇[1,2] 

机构地区：[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

出　　处：《计算机工程与应用》2013年第14期70-72,共3页Computer Engineering and Applications

基　　金：国家自然科学基金(No.70871081);上海市研究生创新基金项目(No.JWCXSL1202)

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。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 diver- sity 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.

关 键 词：萤火虫算法 元胞自动机 多选择背包问题 优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]