A green scheduling algorithm for the distributed flowshop problem
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Date
2021
Authors
Yuan-Zhen Li
Quan-Ke Pan
Kai-Zhou Gao
M. Fatih Tasgetiren
Biao Zhang
Jun-Qing Li
Journal Title
Journal ISSN
Volume Title
Publisher
ELSEVIER
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
In recent years sustainable development and green manufacturing have attracted widespread attention to environmental problems becoming increasingly serious. Meanwhile affected by the intensification of market competition and economic globalization distributed manufacturing systems have become increasingly common. This paper addresses the energy-efficient scheduling of the distributed permutation flowshop (EEDPFSP) with the criteria of minimizing both total flow time and total energy consumption. Considering the distributed and multi-objective optimization complexity an improved NSGAII algorithm (INSGAII) is proposed. First we analyze the problem-specific characteristics and designed new operators based on the knowledge of the problem. Second four constructive heuristic algorithms are proposed to produce high-quality initial solutions. Third inspired by the artificial bee colony algorithm we propose a new colony generation method using the operators designed. Fourth a local intensification is designed for exploiting better non-dominated solutions. The influence of parameter settings is investigated by experiments to determine the optimal parameter configuration of the INSGAII. Finally a large number of computational tests and comparisons have been carried out to verify the effectiveness of the proposed INSGAII in solving EEDPFSP. (c) 2021 Elsevier B.V. All rights reserved. Superscript/Subscript Available
Description
Keywords
Distributed permutation flowshop, scheduling, NSGA-II, Multi-objective optimization, Energy efficient, Total flowtime, Total energy consumption, MINIMIZING MAKESPAN, OPTIMIZATION ALGORITHM, SEARCH ALGORITHM, PERMUTATION, DECOMPOSITION, HEURISTICS
Fields of Science
0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
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OpenCitations Citation Count
48
Source
Applied Soft Computing
Volume
109
Issue
Start Page
107526
End Page
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CrossRef : 51
Scopus : 62
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Mendeley Readers : 38
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