A New Hybrid Ant Colony Optimization Algorithm for Solving the No-Wait Flow Shop Scheduling Problems
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Date
2018
Authors
Engin, Orhan
Journal Title
Journal ISSN
Volume Title
Publisher
ELSEVIER SCIENCE BV
Open Access Color
Green Open Access
No
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Publicly Funded
No
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.
Description
ORCID
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
Turkish CoHE Thesis Center URL
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
140
Source
APPLIED SOFT COMPUTING
Volume
72
Issue
Start Page
166
End Page
176
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