4.7 Article

A hybrid discrete water wave optimization algorithm for the no-idle flowshop scheduling problem with total tardiness criterion

期刊

EXPERT SYSTEMS WITH APPLICATIONS
卷 146, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2019.113166

关键词

Water wave optimization; No-idle flowshop scheduling problem; Total tardiness; Variable neighborhood search

资金

  1. National Natural Science Foundation of China [61663023]
  2. Key Research Programs of Science and TechnologyCommission Foundation of Gansu Province [2017GS10817]
  3. Lanzhou Science Bureau project [2018-rc-98]
  4. Public Welfare Project of Zhejiang Natural Science Foundation [LQI19E050001]
  5. Wenzhou Public Welfare Science and Technologyproject [G20170016]

向作者/读者索取更多资源

The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an initialize method based on a new priority rule combined with the modified NEH method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP. (C) 2019 Elsevier Ltd. All rights reserved.

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