Permutation flow-shop scheduling problem based on new hybrid crow search algorithm

被引：0
|
作者：
Yan H. [1 ]
Tang W. [1 ]
Yao B. [2 ]
机构：
[1] School of Electrical and Control Engineering, Shaanxi University of Scienceand Technology, Xi’an
[2] Schoolof Electronic Information and Artificial Intelligence, Shaanxi University of Scienceand Technology, Xi’an
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2024年 / 30卷 / 05期
基金：
中国国家自然科学基金;
关键词：
crow search algorithm; local search; permutation flow-shop; population initialization;
D O I：
10.13196/j.cims.2021.0808
中图分类号：
学科分类号：
摘要：
To solve the permutation flow-shop scheduling problem with the objective to minimize makespan more effectively,a New Hybrid Crow Search Algorithm (NHCSA) was proposed.A NEH-based heuristic was modified,based on which a new method was put forward to ameliorate the quality and diversity of the initial population.Then,the Smallest-Position-Value (SPV) rule was adopted to enable the algorithm to deal with discrete scheduling problems.For the iterated greedy algorithm,a method was come up with to adjust the range of re-inserted jobs automatically,a Tie-Breaking (TB) mechanism was embedded,and the improved iterated greedy algorithm was incorporated as a local search scheme for the best job permutation to improve the searching accuracy of the proposed algorithm.Simulations based on the well-known benchmarks were carried out,and the results validated the optimization ability and stability.Especially in the comparisons for Rec19 and Rec25 test cases,only NHCSA achieved the current optimal solutions,which further proves its superiority. © 2024 CIMS. All rights reserved.
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页码：1834 / 1846
页数：12
相关论文
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