基于改进遗传算法的二级分销网络优化模型及求解  

Optimization Model for a Bi-level Distribution Network and its Improved Genetic Algorithm-based Solution

作　　者：先强[1] 刘卫宁[1] 

机构地区：[1]重庆大学计算机学院

出　　处：《重庆师范大学学报（自然科学版）》2008年第3期36-41,共6页Journal of Chongqing Normal University:Natural Science

基　　金：科技部国家科技支撑计划(No.2006BAH02A16)

摘　　要：在分销中心选址中考虑设施成本、运输成本、库存成本等要素,以分销中心服务水平为约束条件,提出了随机需求下一个供应商、多个分销中心、多个分销商的二级分销网络的优化模型。采用改进的遗传算法来求解模型,建立了一种精简的编码方式,有效降低了染色体的存储空间。构造了一种随进化代数动态调整的非线性适应度函数,遗传算子采用进化(μ+λ)选择,混合杂交和混合变异方式,从而有效地避免算法的早熟现象,提高了算法的运行效率。最后数值模拟的结果验证了在随机需求下二级分销网络的优化模型的正确性和算法的有效性。With a comprehensive consideration of the facilities fixed costs, transportation costs, inventory costs, and other factors of the distribution center location, under the restriction of service levels at the distribution centers, we propose an optimization programming model of bi-level distribution network with a supplier, multi-distribution centers and multi-retailers under stochastic demand. We adopt improved genetic algorithm to solve the optimization programming model of bi-level distribution network, and establish a succinct coding mode to decrease the memory space of the chromosome. In the meantime, we put forward a nonlinear fitness function which can dynamically adapt to evolutionary process of algorithm, and the genetic operation is involved with evolution （μ ＋ A ） selection, blend crossover and blend mutation modes. Accordingly, in this way we can avoid algorithmic premature and advance the process efficiency. The out- come of the numerical simulation is given to confirm the correctness of the optimization model for a bi-level distribution network under stochastic demand and to testify the effectiveness of the Genetic Algorithm.

关 键 词：二级分销网络 优化 选址 遗传算法 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]