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基于多目标 Pareto 混合优化遗传算法的配送中心货位优化研究—以迪卡侬(昆山)配送中心为例
Study on Distribution Center Cargo Slot Optimization Based on Multi-objective Pareto Hybrid Genetic Algorithm:In the Case of Decathlon(Kunshan) Distribution Center
【摘要】 阐述了迪卡侬(昆山)配送中心的高层货架区在夜间货物整理时的货位优化问题,根据时间、空间优化目标,建立了该配送中心的货位优化模型,并提出了基于整数编码的多目标Pareto混合遗传算法求解该模型,该算法将共享函数引入小生境技术、精英保留策略和Pareto解集过滤器,增加了群体的多样性、解的多样性,高效地解决物流配送中心货位优化问题。算例结果表明:经过100次迭代后的货位分配方案更有效率,货物出入库的效率比优化前提高了52.02%,货架的稳定性提高了64.31%,货位分配布局更加有序合理。
【Abstract】 In this paper, we illustrated the cargo slot optimization problem of the high- level rack area of the Decathlon(Kunshan) Distribution Center in night- time cargo sorting activities, built the cargo slot optimization model of the distribution center, and proposed a multi- objective Pareto hybrid genetic algorithm based on integer encoding to solve it. Then using a numerical example, we demonstrated that the cargo slot allocation plan derived using the algorithm proposed could lead to more efficient inbound and outbound operation and cargo slot arrangement.
【Key words】 distribution center; genetic algorithm; multi-objective Pareto hybrid genetic algorithm; cargo slot optimization;
- 【文献出处】 物流技术 ,Logistics Technology , 编辑部邮箱 ,2013年23期
- 【分类号】F259.27;F721;F224
- 【被引频次】5
- 【下载频次】330