U.S.-Argentina Cooperative Research: Production Planning and Operations Scheduling Algorithms for Multipurpose Batch Plants Producing a Large Number of Low-Volume Products

美国-阿根廷合作科学奖 将支持伊格纳西奥的合作 卡耐基梅隆大学的格罗斯曼和 国立大学的Jaime塞尔达 文学的，阿根廷。 该项目旨在 开发新的算法方法， 生产计划与排程 多用途间歇式工厂 同时产品低至中等 需求 这些方法的目标是 及时满足产品需求， 最大限度地减少闲置时间和产品库存。 另一个目标将是发展现实的 解释群体分配的模型 将连续任务分配给单个设备 项目，同时生产中间体 及成品，多次加工 路径和设置/转换时间。 发展 有效的解决方法，模型将是 调查不依赖离散化的 在时域上， 快速启发式技术。 拟议 技术将在专家内部实施 系统外壳可以提供更好的 用户的理解和理解。 这 预计项目将为双方带来好处 将补充现有研究的方面， 卡内基的优化和批处理 梅隆和UNL。

This US-Argentina Cooperative Science award will support the collaboration of Ignacio Grossmann of Carnegie Mellon University and Jaime Cerda of the Universidad Nacional del Litoral (UNL), Argentina. The project aims to develop new algorithmic methodologies for production planning and scheduling of multipurpose batch plants producing simultaneously products of low to medium demand. A goal of these methodologies will be to satisfy product demands on time, but also minimize idle times and product inventories. Another objective will be to develop realistic models that account for assignments of groups of consecutive tasks to a single equipment item, simultaneous production of intermediate and finished products, multiple processing paths, and setup/changeover times. To develop effective solution methods, models will be investigated that do not rely on discretization of the time domain, and that can be enhanced with fast heuristic techniques. The proposed techniques will be implemented within an expert system shell that can provide for better insights and understanding by the user. This project is expected to produce benefits to both sides that will complement existing research in optimization and batch processing at Carnegie Mellon and UNL.