Integrated tactical planning under uncertainty in the supply chain of divergent-type production systems

分散型生产系统供应链不确定性下的综合战术规划

• 批准号: 402043-2011
• 负责人: KazemiZanjani, Masoumeh
• 金额: $ 1.68万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=573135
• 关键词: Integrated; tactical; planning; under; uncertainty

The proposed research program investigates the robustness in supply chain tactical planning in divergent type production systems faced with uncertainty. Tactical planning in a supply chain consists of integrated planning of procurement, production, distribution and sale activities in a network including suppliers, production units, and distribution centers. The divergent-type production systems are featured by the one-to-many recipes. Such production systems are faced usually with different types of uncertainties. The traditional supply chain planning tools are based on deterministic optimization models. The plans proposed by deterministic approaches are not realistic and robust in the presence of future uncertain events and will usually lead to decreased demand fulfillment comparing the promised service level. Adopting robust planning tools can lead to significant improvements in service level, resource utilization, procurement and distribution costs, environmental effects, etc. The main goal of this research program is to develop efficient robust tactical planning models for the supply chain of divergent-type production systems in the presence of uncertainties, such that they can be applied in industry. Other objectives of this research consist of application of the proposed robust tactical planning tool for 1) the softwood supply chain, where we are facing with the non-homogeneity in the characteristics of logs, and 2) in a reverse supply chain focused on the recovery of end-of-life products with uncertain conditions. Stochastic programming and robust optimization approaches will be adopted in order to model the supply chain tactical planning problem under uncertainty. Efficient hybrid solution algorithms based on exact and heuristic methods will also be proposed to solve the resulting models. For each application, we aim to analyze and compare the two robust tactical planning tools in terms of required modeling and computational effort, validity of estimated uncertainty sets, quality of results, and implementation limitations. Whilst the proposed robust tactical planning tools are important for Canadian industries from both economical and social points of view, this research program will also advance the literature of stochastic optimization.

拟议的研究计划调查了面临不确定性的发散类型生产系统中供应链战术计划的鲁棒性。供应链中的战术规划包括在包括供应商，生产单位和分销中心在内的网络中采购，生产，分销和销售活动的综合计划。一对多食谱介绍了不同的生产系统。这种生产系统通常面临着不同类型的不确定性。传统的供应链规划工具基于确定性优化模型。确定性方法提出的计划在未来不确定事件的情况下不现实和健壮，通常会导致比较应许服务水平的需求履行。采用强大的计划工具可以导致服务水平，资源利用，采购和分配成本，环境效果等的显着改善。该研究计划的主要目标是为不同生产的供应链开发有效的强大战术计划模型在不确定性的情况下，可以将它们应用于行业。这项研究的其他目标包括在1）软木供应链中应用提出的强大战术规划工具，在该链中，我们面临着日志特征的不均匀性，以及2）2）在重点恢复的反向供应链中具有不确定条件的寿命末产品。将采用随机编程和强大的优化方法，以模拟不确定性下的供应链战术计划问题。还将提出基于精确和启发式方法的有效混合溶液算法来解决所得模型。对于每个应用程序，我们旨在根据所需的建模和计算工作，估计不确定性集的有效性，结果质量和实施限制来分析和比较两个强大的战术计划工具。尽管从经济和社会的角度来看，拟议的强大战术计划工具对加拿大行业很重要，但该研究计划也将推动随机优化的文献。