差异化高斯双导向差分物流配送优化  

Differentiation Gauss double orientation differential evolution based logistics distribution optimization

作　　者：邓先瑞[1] 于晓慧[1] 李春艳[1] 赵光峰[2] 

机构地区：[1]唐山师范学院计算机科学系,河北唐山063000 [2]唐山师范学院科研处,河北唐山063000

出　　处：《计算机应用研究》2015年第9期2664-2668,共5页Application Research of Computers

基　　金：河北省科技计划项目(13220319D);唐山师范学院博士基金项目(07A01)

摘　　要：针对以往文献中高斯变异差分进化算法变异方式的导向性过于单一,不利于算法种群结构多样性保持,种群进化信息吸取过于单调的弱点,设计了一种差异化高斯双导向差分进化算法。采用向量图分析方法设计了一种新的高斯双导向变异方式,该变异方式能够兼顾全局进化、局部进化及个体进化信息,以当前全局最优值和个体历史最优值作为个体进化的两个不同导向,从而使变异后的个体能够吸收更多的种群进化有利信息并加以利用,并且根据种群个体进化差异化程度选取合适的变异方式。对差异化高斯双导向差分进化算法的性能进行计算机仿真设计验证,并对算法的物流配送优化问题进行研究。According to the differential evolution improvement oriented mutation by Gauss sampling too single in the previous literature, was not conducive to the algorithm to maintain the population diversity structure, population evolution information learned too monotonous weaknesses, this paper designed a kind of difference Gauss double guide differential evolution algo- rithm. Firstly, using the vector analysis method to design a new Gauss dual oriented variation, which could take into account the overall evolution, individual local evolution and evolutionary information, took the current global optimal value and the optimal value of individual history as two different guiding the individual evolution, so that the mutated individual could absorb more advantage information of population evolutionary and made use, and chose the right mutation operation according to the individ- ual. Then, verify the performance of differentiation Gauss double orientation differential evolution by computer simulation, and applies it to the logistics distribution optimization.

关 键 词：差分进化 差异化 高斯 双导向 物流配送 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]