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A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems

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Abstract

Cuckoo search (CS) is a recently developed meta-heuristic algorithm, which has shown good performance on many continuous optimization problems. In this paper, we present a new CS algorithm, called NCS, for solving flow shop scheduling problems (FSSP). The NCS hybridizes four strategies: (1) The FSSP is a typical NP-hard problem with discrete characteristics. To deal with the discrete variables, the smallest position value (SPV) rule is employed to convert continuous solutions into discrete job permutations; (2) To generate high quality initial solutions, a new method based on the Nawaz-Enscore-Ham (NEH) heuristic is used for population initialization; (3) A modified generalized opposition-based learning (GOBL) is utilized to accelerate the convergence speed; and (4) To enhance the exploitation, a local search strategy is proposed. Experimental study is conducted on a set of Taillard’s benchmark instances. Results show that NCS obtains better performance than the standard CS and some other meta-heuristic algorithms.

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Acknowledgments

This work is supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions, the Humanity and Social Science Foundation of Ministry of Education of China (No. 13YJCZH174), the National Natural Science Foundation of China (Nos. 61305150 and 61261039), and the Natural Science Foundation of Jiangxi Province (No. 20142BAB217020).

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Authors and Affiliations

  1. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Hui Wang

  2. School of Information Engineering, Nanchang Institute of Technology, Nanchang, 330099, China

    Hui Wang & Hui Sun

  3. School of Business Administration, Nanchang Institute of Technology, Nanchang, 330099, China

    Wenjun Wang

  4. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, 030024, China

    Zhihua Cui

  5. Department of Electrical, Computer, and Software Engineering, University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, ON, L1H 7K4, Canada

    Shahryar Rahnamayan

  6. School of Computer Science, China University of Geosciences, Wuhan, 430074, China

    Sanyou Zeng

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  1. Hui Wang
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Correspondence to Hui Wang.

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Wang, H., Wang, W., Sun, H. et al. A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems. Soft Comput 21, 4297–4307 (2017). https://doi.org/10.1007/s00500-016-2062-9

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