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: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=529398
• 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不同类型生产系统中供应链战术规划的稳健性。供应链中的战术规划包括在包括供应商、生产单位和配送中心在内的网络中对采购、生产、分销和销售活动的综合规划。发散型生产系统的特点是一对多配方。这样的生产系统通常面临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。在存在未来不确定事件的情况下，确定性方法提出的计划并不现实和稳健，并且通常会导致与承诺的服务水平相比需求满足率下降。采用稳健的规划工具可以显着改善服务水平、资源利用率、采购和分销成本、环境影响等。本研究项目的主要目标是为存在不确定性的发散型生产系统供应链开发高效稳健的战术规划模型，以便在工业中应用。本研究的其他目标包括将所提出的稳健战术规划工具应用于 1）软木供应链，我们面临着原木特性的非同质性，2）在逆向供应链中，重点关注不确定条件下的报废产品的回收。将采用随机规划和鲁棒优化方法来对不确定性下的供应链战术规划问题进行建模。还将提出基于精确和启发式方法的高效混合求解算法来求解所得模型。对于每个应用程序，我们的目标是在所需的建模和计算工作量、估计不确定性集的有效性、结果质量和实施限制方面分析和比较这两种强大的战术规划工具。虽然从经济和社会角度来看，拟议的稳健战术规划工具对加拿大工业都很重要，但该研究计划也将推动随机优化文献的发展。