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卡内基梅隆大学的伊格纳西奥·格罗斯曼和阿根廷国立大学(UNL)的Jaime Cerda的合作。该项目旨在为同时生产低到中等需求的产品的多用途间歇工厂的生产计划和调度开发新的算法方法。这些方法的一个目标是按时满足产品需求，但也最大限度地减少空闲时间和产品库存。另一个目标是开发现实的模型，说明将连续任务组分配给单个设备项目、同时生产中间产品和成品、多条加工路径以及安装/转换时间。为了开发有效的求解方法，将研究不依赖于时间域离散化的模型，并且可以使用快速启发式技术来增强模型。拟议的技术将在一个专家系统外壳内实施，该外壳可以为用户提供更好的见解和理解。该项目预计将给双方带来好处，补充卡内基梅隆大学和联合国大学在优化和批处理方面的现有研究。

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.