A New Hybrid Ant Colony Optimization Algorithm for Solving the No-Wait Flow Shop Scheduling Problems

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Date

2018

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Volume Title

Publisher

ELSEVIER SCIENCE BV

Open Access Color

Green Open Access

No

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Top 1%
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Top 10%
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Top 1%

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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

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

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Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

Q1

Scopus Q

Q1
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OpenCitations Citation Count
140

Source

APPLIED SOFT COMPUTING

Volume

72

Issue

Start Page

166

End Page

176
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Scopus : 167

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Mendeley Readers : 90

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