A novel mixed integer programming formulation and progressively stochastic search for capacitated lot sizing |
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Authors: | Tao Wu Defu Zhang Yan He |
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Institution: | 1. Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison 2. Department of Computer Science, Xiamen University, 361005, China 3. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400030, China |
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Abstract: | The capacitated multi-level lot sizing problem is to schedule a number of different items with a bill-of-materials structure over a horizon of finite periods. To advance techniques of solving this class of problems, this paper proposes a new mixed integer programming formulation. Theoretical proofs and computational tests are provided to show that this formulation is able to provide better linear programming relaxation lower bounds than a previously-proposed strong mixed integer programming formulation. Based on the new strong formulation, a progressively stochastic search approach is proposed for solving the problem. Computational results showed that the approach generates high quality solutions, especially for problems of large sizes. |
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Keywords: | Capacitated multi-level lot sizing optimization mixed integer programming facility location |
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