U.S.-France Cooperative Research (INRIA): Perturbation Analysis and Parallel Computing for Production Management

该项目为期三年，支持美国马里兰大学的Ioannis Minis和法国国家计算机科学与应用数学研究所（INRIA）的Jean-Marie Proth在运筹学和生产系统方面的合作研究。目标是开发一个系统，促进复杂制造系统的有效和高效的生产计划。调查人员将研究一个多产品生产计划问题。该问题解决了一种确定在多个时间段内要生产的产品数量以使成本函数最小化的方法。研究人员建议使用参数化的分层生产管理系统来处理众多变量，并解释扰乱生产的随机事件。在这种方法中，他们将聚合时间单位、机器和部件类型，以减小问题的规模。在计算出聚合问题的解后，他们提出求解对应于每组机器的子问题，以实现接近最优的详细生产计划。美国研究人员在优化和扰动分析、生产层次和聚合方案方面为这次合作带来了相当多的专业知识。这是由法国调查员在生产计划和调度，并行计算方面的专业知识以及他在制造业的实践经验所补充的。

This three-year award supports U.S.-France cooperative research in operations research and production systems between Ioannis Minis of the University of Maryland and Jean-Marie Proth of INRIA (French National Institute for Research in Computer Science and Applied Mathematics) in Lorraine, France. The objective is to develop a system that facilitates effective and efficient production planning for complex manufacturing systems. The investigators will study a multi-product production planning problem. The problem addresses a way to determine the number of products to be manufactured over many time periods in order to minimize the cost function. The investigators propose to use a parameterized hierarchical production management system to deal with the numerous variables and account for random events that disrupt production. In this approach they will aggregate the time units, the machines, and the part types in order to reduce the size of the problem. After computing a solution for the aggregated problem, they propose to solve the subproblems corresponding to each group of machines in order to achieve a near-optimal detailed production plan. The U.S. investigators bring to this collaboration considerable expertise in optimization and perturbation analysis, production hierarchy, and aggregation schemes. This is complemented by the French investigator's expertise in production planning and scheduling, parallel computing, and his practical experience in manufacturing.