Abstract: This paper proposes a novel multiobjective evolutionary algorithm inspired by quantum 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.

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。