装配型企业订货量分配与订单排产联合决策研究

发布时间：2018-10-05 21:38

【摘要】：针对供应商交货数量不确定环境下,多品种小批量装配型制造企业因生产物料不配套造成生产计划不可行甚至客户订单拖期的问题,从企业运作整体出发,考虑订货量分配决策对订单生产和交货的影响,以最小化采购成本和最小化订单排产相关成本为优化目标,在允许零部件拖期交货且供应商提供拖期价格折扣条件下,建立订货量分配与订单排产联合优化模型。针对可行解空间巨大、传统数学规划方法难以求解的问题,从增强搜索性能角度出发,设计基于自定义邻域搜索算子的局部搜索机制和基于随机与种群重构变异机制的改进粒子群算法的模型求解策略。通过应用实例对本文模型和算法进行了有效性验证和灵敏度分析,结果表明,相比于传统的分散决策方案,本文模型能够有效降低整体成本水平,引入的改进机制能够显著提升算法搜索性能,为企业供应风险下的运营决策制定提供理论参考。
[Abstract]:In view of the problem that the production plan is not feasible or even the customer order is delayed due to the unmatched production materials in the multi-variety and small-batch assembly enterprises under the uncertain delivery quantity of suppliers, the whole operation of the enterprise is considered. Considering the impact of order allocation decision on order production and delivery, minimizing purchase cost and order scheduling related cost is the optimization objective, under the condition that parts are allowed to be delivered late and suppliers provide delayed price discount. The optimal model of order quantity distribution and order scheduling is established. In view of the problem that the feasible solution space is huge and the traditional mathematical programming method is difficult to solve, from the point of view of enhancing the search performance, The local search mechanism based on self-defined neighborhood search operator and the model solving strategy of improved particle swarm optimization algorithm based on random and population reconstruction mutation mechanism are designed. The validity and sensitivity of the model and algorithm are verified and analyzed by an example. The results show that compared with the traditional decentralized decision scheme, the model can effectively reduce the overall cost level. The improved mechanism can significantly improve the search performance of the algorithm and provide a theoretical reference for the operation decision making under the supply risk.
【作者单位】：大连理工大学管理与经济学部;
【基金】：国家科技支撑计划资助项目(2015BAF08B02)
【分类号】：F274

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