联合采购策略下企业“选址-库存-配送”低碳协同优化模型研究

With the favored of joint replenishment strategy in the company, the location and delivery decision of distribution center becomes a problem needs to be solved immediately. However, the decision of the problem is still in traditional method without considering collaborative optimizing based on joint replenishment strategy. In reaction to the phenomenon, the objective of this project is to discuss the low-carbon collaborative optimizing of location-inventory-delivery based on joint replenishment strategy(JR-LID) to pursuit the balance between economy and environment.(1) A collaborative optimization model of JR-LID is built through the recognizing of key factors of enterprise operating, the analyzing of core of joint replenishment strategy, and its integrated with location and delivery. The carbon emission of supply chain can be controlled through these optimized operating. (2) The apparent control of carbon emission in inventory and delivery process can be achieved by adding condition constrain/objective constrain in above model. (3) A novel intelligent algorithm called fireworks algorithm is chosen to solve these complex models after improved. The improved algorithm will resolve the models efficient and stably. (4) The management insights can be obtained by analyzing the application condition of different collaborative mode. And the results can be convert to prototype system to provide aid for decision-makers.

随着各大企业对联合补货策略的青睐，如何在联合采购策略下，合理有效进行配送中心选址、安排配送就成为急需解决的问题。但目前，相关决策理论仍停留在传统方式，没有融入联合补货策略进行协同优化。针对这一现象，本项目在新时代背景下，基于联合补货策略，探讨企业的选址-库存-配送低碳协同优化方案，寻求经济和环境的协同发展。（1）识别企业运作关键影响因素，分析联合补货策略核心思想及与选址、配送决策的融合方式，构建基于联合补货策略的选址-库存-配送协同优化模型。通过优化运作方式，隐式控制整个供应链的碳排放量；（2）对仓储及配送环节的碳排放量进行显式控制，对以上协同优化模型进行低碳条件约束和目标约束；（3）针对模型复杂度，选取新颖的烟花算法，针对性地进行改进设计，为模型求解提供高效稳定的算法支持；（4）分析不同协同优化方式的适用范围，得到科学的管理启示，并将结果转换为可操作的原型系统，为企业提供辅助决策。

随着大数据技术、人工智能的不断发展，数据的可获取性及可操作性越来越强，企业自建配送中心或与其他企业组成企业联盟构建联采联配一体化的集成运作模式已成为一种趋势。但目前，相关决策理论仍停留在传统方式，理论研究滞后于企业现实需求。本项目（1）从运作方式优化、低碳约束两种视角研究联合补货策略（JR）下的选址、库存、配送协同优化问题：①研究了间接分组策略下考虑配送路径的联采联配问题，实现配送中心对联采物品的全协同配送，有效提高车辆利用率。②数量折扣在联采联配环节具有极大的应用优势，但同时也面临着运输资源的限制，基于此研究了带数量折扣和资源限制的库存与配送协同优化问题；③弥补联合补货策略下选址-库存-配送协同优化问题研究的不足，构建了确定需求下单物品JR-LID优化模型和低碳约束下的多物品JR-LID优化模型；④鉴于联合补货策略在企业/行业的广泛应用，联合补货品种和规模会不断增加，为解决求解效率瓶颈，研究了烟花算法在大规模联合补货问题中的应用效果，并拓展构建考虑碳排放目标约束的JRP模型，进一步验证烟花算法求解此类问题的性能。（2）鉴于JRP及其拓展模型的NP-hard性质，剖析模型性质，基于烟花算法、差分进化算法，并结合启发式方法，巧妙设计科学合理的求解方案，实验结果验证了所设计算法的性能优势。（3）模型应用效果分析。通过设计不同运作模式的对比实验、成本参数敏感性实验，探索不同优化策略的适用条件以及成本参数、环境因素对系统总成本、运作决策的影响，得到科学的管理启示，为企业提供辅助决策。