Minimizing makespan for the distributed hybrid flowshop scheduling problem with multiprocessor tasks

•This paper is the first research to solve the distributed hybrid flowshop scheduling problem.•The proposed SIG algorithm provides a practical means of solving this problem.•This study contributes significantly to expand the research on distributed scheduling problems. The trend of globalization has...

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Bibliographic Details
Published in:Expert systems with applications Vol. 92; pp. 132 - 141
Main Authors: Ying, Kuo-Ching, Lin, Shih-Wei
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.02.2018
Elsevier BV
Subjects:
Adaptive algorithms
Adaptive cocktail decoding mechanism
Algorithms
Decoding
Distributed hybrid flowshop
Globalization
Greedy algorithms
Integer programming
Linear programming
Mixed integer
Multiprocessing
Scheduling
Scheduling algorithms
Self-tuning iterated greedy algorithm
Task scheduling
Adaptive cocktail decoding mechanism
Self-tuning iterated greedy algorithm
Scheduling
Distributed hybrid flowshop
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:•This paper is the first research to solve the distributed hybrid flowshop scheduling problem.•The proposed SIG algorithm provides a practical means of solving this problem.•This study contributes significantly to expand the research on distributed scheduling problems. The trend of globalization has recently seen the study of distributed scheduling problems. This study attempts to solve the distributed hybrid flowshop scheduling problem with multiprocessor tasks, and is the first attempt to address this problem. To solve this strongly NP-hard problem, a mixed integer linear programming formulation and self-tuning iterated greedy (SIG) algorithm that incorporates an adaptive cocktail decoding mechanism are presented to minimize the makespan. Comprehensive computational results demonstrate that the proposed SIG algorithm is extremely efficient and effective. This paper successfully expands the research area of distributed scheduling problems.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2017.09.032