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工程科学与技术:2014,46(6):38-43
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一种新的混合差分粒子群优化算法及其应用
(湖北民族学院计算机科学与技术系)
New HybridDifferentialEvolutionandParticleSwarmOptimizationAlgorithmandItsApplication
(Dept.ofComputerSci.&Technol.,HubeiMinzuUniv.)
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投稿时间:2014-06-27    修订日期:2014-08-31
中文摘要: 针对B2C电子商务物流配送优化精度不高的问题,提出基于一种新的混合差分粒子群启发式优化算法的B2C电子商务物流配送优化方案。首先,将粒子群种群作为辅助变异算子与差分进化算法种群进行交叉操作,产生的新子代继承了父代和母代的优势特性,从而避免了单一算法的早熟收敛和收敛速度过慢的问题。通过与已有的改进算法仿真对比,该算法能够有效地跳出局部极值,防止算法早熟且收敛速度很快。其次,借鉴已有文献方法对混合算法在B2C路径优化问题中的工程应用进行了实验研究,通过仿真显示所设计配送方案具有更快的计算速度和更优的目标收敛值。
Abstract:In order to solve the problem that the B2C electronic commerce logistics distribution optimization accuracy is not high, a new hybrid differential evolution and particle swarm optimization heuristic optimization algorithm based B2C e-commerce logistics distribution optimization was proposed. Firstly, the particle swarm population was used as auxiliary mutation operator to do the crossover operation with differential evolution algorithm population, resulting new generation that inherits the advantages of characteristics of parents, thus avoiding the single algorithm premature convergence and low convergence rate. Through simulation comparison with the other existing improved algorithm, the algorithm here can effectively escape from local minima, prevent premature convergence, and the convergence is fastest. The simulation showed the designed distribution scheme has the faster calculation speed and better convergence of the target value.
文章编号:201400706     中图分类号:    文献标志码:
基金项目:国家自然科学基金资助项目(61173175; 61262078)
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沈济南,梁芳,郑明辉.一种新的混合差分粒子群优化算法及其应用[J].工程科学与技术,2014,46(6):38-43.
Shen Ji’nan,Liang Fang,Zheng Minghui.New HybridDifferentialEvolutionandParticleSwarmOptimizationAlgorithmandItsApplication[J].Advanced Engineering Sciences,2014,46(6):38-43.