【摘要】 在分析基本粒子群优化算法和建立虚拟企业伙伴选择多目标决策模型的基础上,提出了一种求解供应链联盟伙伴选择的优化问题的改进粒子群算法。在优化过程中,该算法以优良适应值粒子取代部分不良适应值粒子,使算法具有过滤能力,加快了搜索速度,并保证了收敛于全局最优解。实验结果用基本粒子群算法进行了验证和比较,表明该改进粒子群算法具有较好的性能和简单快速准确等特点。更多还原

【Abstract】 On the basis of analyzing the particle swarm optimization(PSO) algorithm and establishing the multi-objective decision-making model for partner selection,an improved PSO algorithm is presented to the optimize partner selection problems in a supply chain alliance.By replacing the particles with worse fitness values with the feasible particles with better fitness values during the process of optimization,the algorithm has the ability of filtrating,and the searching speed is improved,which can guarantee the global optimal solution being found as well.Moreover,effective performance and experimental results are rapidly obtained through the improved PSO algorithm,which can be confirmed by the method of basic PSO algorithm.更多还原