Hybrid constraint generation approaches for industrial scheduling and logistics

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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.