Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/544
Title: | A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems | Authors: | Engin, Orhan Güçlü, Abdullah |
Keywords: | Scheduling No-Wait Flow Shop Hybrid Ant Colony Algorithm Makespan Particle Swarm Optimization Iterated Greedy Algorithm Total Completion-Time Makespan Criterion Genetic Algorithms Minimize Makespan Setup Times In-Process Flowshops Search |
Publisher: | ELSEVIER SCIENCE BV | Abstract: | This paper proposes an effective new hybrid ant colony algorithm based on crossover and mutation mechanism for no-wait flow shop scheduling with the criterion to minimize the maximum completion time. The no-wait flow shop is known as a typical NP-hard combinational optimization problem. The hybrid ant colony algorithm is applied to the 192 benchmark instances from literature in order to minimize makespan. The performance of the proposed Hybrid Ant Colony algorithm is compared to the Adaptive Learning Approach and Genetic Heuristic algorithm which are used in previous studies to solve the same set of benchmark problems. The computational experiments show that the proposed Hybrid Ant Colony algorithm provides better results relative to the other algorithms. (C) 2018 Elsevier B.V. All rights reserved. | URI: | https://doi.org/10.1016/j.asoc.2018.08.002 https://hdl.handle.net/20.500.13091/544 |
ISSN: | 1568-4946 1872-9681 |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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1-s2.0-S1568494618304502-main.pdf Until 2030-01-01 | 1.4 MB | Adobe PDF | View/Open Request a copy |
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