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

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Publisher

Springer Nature

Open Access Color

GOLD

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No

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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).

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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

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Fields of Science

0211 other engineering and technologies, 02 engineering and technology

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OpenCitations Citation Count
15

Source

SN Applied Sciences

Volume

3

Issue

6

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CrossRef : 8

Scopus : 16

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SCOPUS™ Citations

16

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Web of Science™ Citations

14

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