A Hybrid Genetic Local and Global Search Algorithm for Solving No-Wait Flow Shop Problem With Bi Criteria
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Date
2021
Authors
Engin, Orhan
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Nature
Open Access Color
GOLD
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
This paper addresses the m-machine no-wait Flow Shop Scheduling with Setup Times (NW-FSSWST). Two performance measures: total flow time and makespan are considered. The objective is to find a sequence that minimizing total flow time (? Cj) and makespan (Cj) simultaneously. A Hybrid Genetic Local and Global Search Algorithm (HGLGSA) is proposed to solve the NW-FSSWST for two performance criteria. The hybrid genetic algorithm is constructed by insert-search and self-repair algorithm with self-repair function. The proposed HGLGSA is tested on 192 benchmark problems of NW-FSSWST in the literature. A full factorial experimental design is made for determined the best parameter sets that improve the performance of the proposed algorithm. The computational results are compared with the benchmark solutions from the literature. The experimental results demonstrate the effectiveness and efficiency of the proposed HGLGSA for solving NW-FSSWST. © 2021, The Author(s).
Description
Keywords
Global search, Hybrid genetic algorithm, Insert-search, Local search, Makespan, No-wait flow shop scheduling, Self-repair, Total flow time, Global search, Technology, Makespan, No-wait flow shop scheduling, Hybrid genetic algorithm, Science, T, Q, Total flow time, Local search
Turkish CoHE Thesis Center URL
Fields of Science
0211 other engineering and technologies, 02 engineering and technology
Citation
WoS Q
Scopus Q
N/A

OpenCitations Citation Count
15
Source
SN Applied Sciences
Volume
3
Issue
6
Start Page
End Page
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CrossRef : 8
Scopus : 16
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Mendeley Readers : 14
SCOPUS™ Citations
16
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Web of Science™ Citations
14
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