Strategic Reverse Production System Design

这笔赠款提供资金，用于开发设计和推广反向生产系统的方法和工具。方法论基础是数学规划，特别是混合整数线性规划。该模型使用一个稳健的目标函数来最小化一组情景下稳健解与最优解的最大偏差。该方法在四个方面建立在以前对逆向生产系统的研究基础上。首先，它将系统的范围扩展到覆盖前向生产系统中的决策。其次，它考虑了多种大宗商品。第三，它对对决策有重大影响的不确定性进行了更丰富的表示。第四，它解决了反向生产系统，其中有几个独立的参与者，它们的目标可能相互冲突。主要调查人员和参与地毯和电子产品回收的组织之间的密切联系将使这些工具能够在各种情况下进行测试和改进。支持材料和子部件在使用寿命结束时回收、加工和转售的生产系统是美国和世界经济的重要组成部分。据估计，有73,000家公司雇佣了350,000人，仅在再制造方面就创造了530亿美元/年的收入。与公司、非营利组织和政府机构合作，研究的成功结果使战略逆向生产系统设计能够更好地决策，并实际应用于地毯和电子行业的回收和再利用。它们将通过使问题表示更丰富，并通过开发在供应链设计背景下解决大规模数学规划问题的新方法，为复杂供应链决策的知识库做出贡献。学生和我们的工业伙伴将接触到对现代工业化社会具有重要意义的大量问题，以及一套可以应用于广泛决策问题的技术。

This grant provides funding to develop methodology and tools for the design and extension of reverse production systems. The methodological basis is mathematical programming, specifically mixed-integer linear programming. The model uses a robust objective function that minimizes the maximum deviation of the robust solution from the best solutions for a set of scenarios. The approach builds on previous research in reverse production systems in four ways. First, it extends the scope of the system to overlay decisions in the forward production system. Second, it considers multiple commodities. Third, it develops richer representations of uncertainties that have a major impact on the decision-making. Fourth, it addresses reverse production systems with several independent players that may have conflicting goals. The strong links between the principal investigators and organizations involved in recycling for carpet and electronics will allow these tools to be tested and refined in a variety of contexts. Production systems that support the recovery, processing and resale of materials and sub-components at the end of their useful life are an important part of the U.S. and world economy. There are estimated to be 73,000 firms employing 350,000 people, generating revenues of US$53 billion/year in remanufacturing alone. Working with companies, non-profits, and government agencies, successful results from the research enable better decision making for strategic reverse production system design, with practical application to recycling and reuse in the carpet and electronics industry. They will contribute to the knowledge base for complex supply chain decision-making, both by making the problem representation richer, and by developing new approaches for solving large-scale mathematical programming problems in the context of supply chain design. The students and our industrial partners will gain exposure to a rich class of problems of significant importance to modern industrialized societies and a set of techniques that can be brought to bear on a wide range of decision-making problems.