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An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flowshop Problem in Steelmaking Process

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5 Author(s)
Quan-Ke Pan ; State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China ; Ling Wang ; Kun Mao ; Jin-Hui Zhao
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This paper aims to provide a solution method for the real-world hybrid flowshop scheduling problem resulting from a steelmaking process, which has important applications in modern iron and steel industry. We first present a mixed integer mathematic model based on a comprehensive investigation. Then, we develop a heuristic method and two improvement procedures for a given schedule based on the problem-specific characteristics. Finally, we propose an effective artificial bee colony (ABC) algorithm with the job-permutation-based representation for solving the scheduling problem. The proposed ABC algorithm incorporates the heuristic and improvement procedures as well as new characteristics including a neighboring solution generation method and two enhanced strategies. To evaluate the proposed algorithm, we present several adaptations of other well-known and recent metaheuristics to the problem and conduct a serial of experiments with the instances generated according to real-world production process. The results show that the proposed ABC algorithm is more effective than all other adaptations after comprehensive computational comparisons and statistical analysis.

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IEEE Transactions on Automation Science and Engineering  (Volume:10 ,  Issue: 2 )