摘要
针对二次背包问题,提出一种新的基于群体智能的随机扩散算法.算法采用一对一的通信机制;利用部分函数估计评价候选解;利用量子机制构造个体;采用1-OPT和异或操作提高搜索性能.通过数值实验并与微粒群算法、蚁群算法作比较,结果表明算法具有较好的优化性能.
To solve the quadratic knapsack problem, we propose a stochastic diffusion search algorithm which is a novel algorithm based on swarm intelligence. This algorithm adopts one-to-one communication mechanism. The candidate solutions are estimated by the partial function evaluation. Individuals are produced by quantum computation. 1-OPT and XOR operations are employed to improve the search ability, Comparison of the experiment results with those obtained from the particle swarm optimization and the ant colony optimization shows that the proposed algorithm is more effective.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2011年第8期1140-1144,共5页
Control Theory & Applications
基金
国家自然科学基金资助项目(70871081)
上海市重点学科建设资助项目(S30504)
关键词
一对一通信
部分函数估计
二次背包问题
one-to-one communication
partial function evaluation
quadratic knapsack problem
