摘要
提出一种求解离散优化的量子差分进化算法,将逻辑运算引入到算法中,采用量子理论中的叠加态特性增强群体的多样性,基于突变论的思想采用突变操作防止群体陷入局部最优,算法具有较好的全局优化能力。通过二次背包问题的实验和与其他算法的比较,说明算法的可行性和有效性。
A quantum differential evolution is proposed for discrete optimization.The population diversity is increased by superposition characteristic. Based on the idea of catastrophe theory, the algorithm uses mutation operation to avoid falling into local optimum. The algorithm has stronger global optimization capability .The results of experiments on quadratic knapsack problem and comparison with other algorithms show that the algorithm is feasible and effective.
出处
《微计算机信息》
2010年第27期203-204,共2页
Control & Automation
关键词
量子
差分进化
二次背包问题
quantum
differential evolution
quadratic knapsack problem
