Hybrid constraint generation approaches for industrial scheduling and logistics

货物运输（即，物流）和制造过程的调度形成了加拿大经济的两个关键要素。在实践中，在研究文献中，运筹学技术，如混合整数规划，约束规划，和数学，适用于这样的问题。在过去的15年里，PI为混合约束生成方法的研究和开发做出了贡献，这些方法用于解决硬组合问题，包括物流和调度。这种技术依赖于一个问题的分解和子问题之间的约束条件的交换，以确保最佳的解决方案或解决方案的质量guarantees可以found.Evidence在文献中指出，这样的技术往往实现一个或两个数量级的增加，解决问题的能力相比，传统的方法。 该项目将进一步开发四个物流和调度问题的混合约束生成技术，这些问题目前由工业合作伙伴Visual Thinking International Ltd通过传统方法解决：五大湖库存路由，电镀线排序，线圈修剪优化和批量优化。这些都是现实世界的核心问题，是相关的许多制造和物流公司，并已在文献中进行了研究，但没有约束生成技术已经开发。 该项目将（1）将PI在学术文献中开发的技术转让给加拿大软件公司，（2）通过利用工业合作伙伴的数据解决工业规模问题的挑战，进一步开发约束生成方法。

The transportation of goods (i.e., logistics) and the scheduling of manufacturing processes form two key elements in the Canadian economy. In practice, and in the research literature, Operations Research techniques, such as mixed integer programming, constraint programming, and heuristics, are applied to such problems. Over the past 15 years, the PI has contributed to the research and development of hybrid constraint generation approaches to hard combinatorial problems, including logistics and scheduling. Such techniques rely on a problem decomposition and the exchange of constraints amongst the sub-problems to ensure that optimal solutions or solution quality guarantees can be found. Evidence in the literature points to such techniques often achieving one or two orders-of-magnitude increase in problem solving power compared to traditional approaches. This project will further develop hybrid constraint generation techniques for four logistics and scheduling problems that are currently solved by traditional approaches by the industrial partner, Visual Thinking International Ltd: Great Lakes Inventory Routing, Sequencing for Plating Lines, Coil Trim Optimization, and Batch Optimization. These are real-world versions of core problems that are relevant to many manufacturing and logistics companies and have been studied in the literature, but for which no constraint generation techniques have been developed. The project will (1) transfer the technology that the PI has been part of developing in the academic literature to a Canadian software company and (2) further develop the constraint generation approach through the challenge of addressing the industrial-scale problems via data from the industrial partner.