A decomposition approach for the scheduling of a steel plant production |
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| Authors: | Iiro Harjunkoski Ignacio E. Grossmann |
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| Affiliation: | 1. School of materials science and engineering, Chongqing University, Chongqing, China;2. School of Economics and Business Administration, Chongqing University, Chongqing, China;1. School of Management Science and Engineering, Anhui University of Technology, Ma''anshan, Anhui 243032, China;2. Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes, Anhui University of Technology, Ma''anshan, Anhui 243032, China;1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, PR China;2. School of Computer Science, Liaocheng University, Liaocheng 252000, PR China;3. State Key Lab of Digital Manufacturing Equipment & Technology in Huazhong University of Science & Technology, Wuhan 430074, PR China;4. Department of Automation, Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing 100084, PR China |
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| Abstract: | In this paper we present a decomposition strategy for solving large scheduling problems using mathematical programming methods. Instead of formulating one huge and unsolvable MILP problem, we propose a decomposition scheme that generates smaller programs that can often be solved to global optimality. The original problem is split into subproblems in a natural way using the special features of steel making and avoiding the need for expressing the highly complex rules as explicit constraints. We present a small illustrative example problem, and several real-world problems to demonstrate the capabilities of the proposed strategy, and the fact that the solutions typically lie within 1–3% of the global optimum. |
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| Keywords: | Mixed Integer Programming Steel making Scheduling Heuristics Disaggregation |
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