Abstract
A common problem in production planning is to sequence a series of tasks so as to meet demand while satisfying operational constraints. This problem can be challenging to solve in its own right. It becomes even more challenging when higher-level decisions are also taken into account, such as which shifts should be selected to accommodate production. In this paper, we introduce the Shift-Selection and Task Sequencing (SS-TS) problem, develop the hybrid Test-and-Prune algorithm (T&P) to solve SS-TS, and present computational experiments based on a real-world problem in automotive stamping to demonstrate its effectiveness. In particular, we are able to solve, in very short run times, a number of problem instances that could not be solved through traditional integer programming methods.
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Barlatt, A., Cohn, A.M., Gusikhin, O. (2008). A Hybrid Approach for Solving Shift-Selection and Task-Sequencing Problems. In: Perron, L., Trick, M.A. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2008. Lecture Notes in Computer Science, vol 5015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68155-7_24
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DOI: https://doi.org/10.1007/978-3-540-68155-7_24
Publisher Name: Springer, Berlin, Heidelberg
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