Abstract
Steelmaking and the continuous-casting (SCC) scheduling problem is a realistic hybrid flow shop scheduling problem with continuous-casting production at the last stage. This study considers the SCC scheduling problem with diverse products, which is a vital and difficult problem in steel plants. To tackle this problem, this study first presents the mixed-integer linear programming (MILP) model to minimize the objective of makespan. Then, an improved migrating birds optimization algorithm (IMBO) is proposed to tackle this considered NP-hard problem. In the proposed IMBO, several improvements are employed to achieve the proper balance between exploration and exploitation. Specifically, a two-level decoding procedure is designed to achieve feasible solutions; the simulated annealing-based acceptance criterion is employed to ensure the diversity of the population and help the algorithm to escape from being trapped in local optima; a competitive mechanism is developed to emphasize exploitation capacity by searching around the most promising solution space. The computational experiments demonstrate that the proposed IMBO obtains competing performance and it outperforms seven other implemented algorithms in the comparative study.
Highlights
The common flow shop scheduling problem (FSP) is a complex combinatorial optimization problem which has great applications in industry [1,2,3]
This study considers a realistic hybrid flow shop scheduling problem (HFSP) in the steel plants, namely the steelmaking and continuous-casting (SCC) scheduling problem
The proposed improved migrating birds optimization algorithm (IMBO) has three main improvements: (1) the new neighborhood structures are utilized to improve the leader bird and following birds to intensify exploration; (2) a new acceptance criterion is developed to enhance the diversity of the population and help the algorithm to escape from being trapped into local optima; (3) the competitive mechanism is developed to emphasize exploitation capacity by searching around the most promising solution space
Summary
The common flow shop scheduling problem (FSP) is a complex combinatorial optimization problem which has great applications in industry [1,2,3]. The SCC scheduling problem is usually regarded as a hybrid flow shop scheduling problem (HFSP) with continuous-casting production at the last stage. The SCC scheduling problem consists of three stages (steelmaking, refining, and continuous casting) in series, where each stage can have several machines in parallel, and a set of charges are operated by the machines available. This results in the increasing of batch diversity and highly frequent utilization of the refining process These changes further increase the time complexity for solving the SCC scheduling problem, and lead to a large difficulty in developing a reasonable and effective production schedule. This study presents an improved migrating birds optimization algorithm (IMBO) to tackle the SCC scheduling problem with diverse products effectively.
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