Quantum swarm evolutionary algorithm with time-varying acceleration coefficients for partner selection in virtual enterprise

Jian-hua Xiao, Bing-lian Liu
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引用次数: 3

Abstract

Partner selection is one of the most critical issue in virtual enterprise, which has been extensively researched in recent years. It is difficult to be solved by the traditional optimization methods for partner selection is a combinatorial optimization problem. In this paper, an improved quantum swarm evolutionary algorithm based on time-varying acceleration coefficients (IQSEA_TVAC) is proposed for partner selection optimization problem. The results of simulation experiments show that the improved algorithm is valid and outperforms the conventional quantum evolutionary algorithm.
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基于时变加速系数的量子群进化算法的虚拟企业合作伙伴选择
合作伙伴选择是虚拟企业中最关键的问题之一,近年来得到了广泛的研究。合作伙伴选择是一个组合优化问题,是传统优化方法难以解决的问题。本文提出了一种改进的基于时变加速度系数的量子群进化算法(IQSEA_TVAC),用于伙伴选择优化问题。仿真实验结果表明,改进算法是有效的,优于传统的量子进化算法。
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