An improved backtracking search algorithm for casting heat treatment charge plan problem

Jianxin Zhou, Hu Ye, Xiaoyuan Ji () and Weilin Deng
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Jianxin Zhou: Huazhong University of Science and Technology
Hu Ye: Huazhong University of Science and Technology
Xiaoyuan Ji: Huazhong University of Science and Technology
Weilin Deng: Huazhong University of Science and Technology

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 3, No 23, 1335-1350

Abstract: Abstract This study investigates the optimization of the charge plan in casting heat treatment. The optimization problem is formulated as a 0–1 integer programming model aiming at maximizing the utilization of the furnaces, minimizing the holding temperature differences and the overall delivery deadline of castings in a furnace. To approach the mathematical model, a two-steps solution methodology is designed. First, the feasible casting candidate sets are generated in consideration of the holding temperature and cooling mode constraints. Then, an improved backtracking search algorithm (IBSA) is proposed to obtain optimal charge plan for each feasible candidate set. The best one among the optimal charge plans obtained by IBSA is selected as the final charge plan. In IBSA, a mapping mechanism is applied to make original backtracking search algorithm (BSA) suitable to discrete problems. Improvements that consist of the modification of historical population updating mechanism, the hybrid of mutation and crossover strategy of difference evaluation algorithm, a greedy local search algorithm and the re-initialization operator are also made to enhance the exploitation and exploration ability of IBSA. The comparisons of simulation experiments demonstrate the effectiveness of the proposed model and the performance of the proposed algorithm.

Keywords: Charge plan; Heat treatment; Backtracking search algorithm; Difference evaluation; Greedy local search (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-017-1328-0

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