摘要
通过设计一种新的量子个体更新策略,提出了改进的多宇宙并行量子进化算法,并对算法的收敛性进行了分析探讨,从理论上证明了该算法的有效性,最后将该算法用于多目标0/1背包问题。仿真结果表明:改进方法能够找到接近Pareto最优前端的更好的解,同时维持解分布的均匀性。
This paper proposes a novel multiobjective evolutionary algorithm inspired by quantttm computing, which is named Improved Multi-universe Parallel Quantum-inspired Evolutionary Algorithm（IMPQEA）.In the algorithm, a new strategy is designed to update each quantum individuals.Moreover,the convergence of this algorithm is analyzed and the validity in theory is proved.At the end, it is applied to the multiobjective 0/1 knapsack problem.Experimental results show that IMPQEA finds the better solutions close to the Pareto-optimal front while maintaining a uniform spread of nondominated set.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第34期35-38,共4页
Computer Engineering and Applications
基金
安徽省自然科学基金(No.090412072)~~
