A green scheduling algorithm for the distributed flowshop problem
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Date
2021
Authors
Yuanzhen Li
Quanke Pan
Kaizhou Gao
M. Fatih Tasgetiren
Biao Zhang
Junqing Li
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Ltd
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
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. © 2021 Elsevier B.V. All rights reserved.
Description
Keywords
Distributed Permutation Flowshop Scheduling, Energy Efficient, Multi-objective Optimization, Nsga-ii, Total Energy Consumption, Total Flowtime, Competition, Energy Efficiency, Energy Utilization, Heuristic Algorithms, Multiobjective Optimization, Sustainable Development, Artificial Bee Colony Algorithms, Constructive Heuristic Algorithm, Distributed Manufacturing Systems, Economic Globalization, Energy-efficient Scheduling, Environmental Problems, Permutation Flow Shops, Total Energy Consumption, Green Manufacturing, Competition, Energy efficiency, Energy utilization, Heuristic algorithms, Multiobjective optimization, Sustainable development, Artificial bee colony algorithms, Constructive heuristic algorithm, Distributed manufacturing systems, Economic globalization, Energy-Efficient Scheduling, Environmental problems, Permutation flow shops, Total energy consumption, Green manufacturing, Distributed Permutation Flowshop, Total Flowtime, Distributed Permutation Flowshop Scheduling, Scheduling, Energy Efficient, Multi-Objective Optimization, Total Energy Consumption, NSGA-II
Fields of Science
0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
48
Source
Applied Soft Computing
Volume
109
Issue
Start Page
107526
End Page
PlumX Metrics
Citations
CrossRef : 51
Scopus : 62
Captures
Mendeley Readers : 38
SCOPUS™ Citations
62
checked on Apr 09, 2026
Web of Science™ Citations
53
checked on Apr 09, 2026
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