Minimizing the Sum of Makespan and Total Weighted Tardiness in a No-Wait Flowshop

This paper presents a cloud theory-based iterated greedy (CTIG) algorithm for solving the no-wait flowshop scheduling problem (NWFSP) with the objective of minimizing the sum of makespan and total weighted tardiness. The performance of the proposed CTIG algorithm is evaluated by comparing its comput...

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Published in:	IEEE access Vol. 6; pp. 78666 - 78677
Main Authors:	Lin, Shih-Wei, Lu, Chung-Cheng, Ying, Kuo-Ching
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms cloud theory-based iterated greedy algorithm Computing time Flowcharts Greedy algorithms Heuristic methods Indexes Industries Job shop scheduling Job shops metaheuristics no-wait flowshop Particle swarm optimization Scheduling Single machine scheduling Urban areas
ISSN:	2169-3536, 2169-3536
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Abstract	This paper presents a cloud theory-based iterated greedy (CTIG) algorithm for solving the no-wait flowshop scheduling problem (NWFSP) with the objective of minimizing the sum of makespan and total weighted tardiness. The performance of the proposed CTIG algorithm is evaluated by comparing its computational results to those of the best-to-date meta-heuristic algorithm, particle swarm optimization (PSO), as presented in this paper. The experimental results concerning two sets of benchmark problem instances in this paper demonstrate that the CTIG algorithm obtains more (near) optimal solution in less computational time than the PSO algorithm. The computational results in this paper fill the research gap in the development of a novel algorithm to improve the solution quality in the case of the NWFSP with the objective of minimizing the sum of makespan and total weighted tardiness.
AbstractList	This paper presents a cloud theory-based iterated greedy (CTIG) algorithm for solving the no-wait flowshop scheduling problem (NWFSP) with the objective of minimizing the sum of makespan and total weighted tardiness. The performance of the proposed CTIG algorithm is evaluated by comparing its computational results to those of the best-to-date meta-heuristic algorithm, particle swarm optimization (PSO), as presented in this paper. The experimental results concerning two sets of benchmark problem instances in this paper demonstrate that the CTIG algorithm obtains more (near) optimal solution in less computational time than the PSO algorithm. The computational results in this paper fill the research gap in the development of a novel algorithm to improve the solution quality in the case of the NWFSP with the objective of minimizing the sum of makespan and total weighted tardiness.
Author	Lu, Chung-Cheng Lin, Shih-Wei Ying, Kuo-Ching
Author_xml	– sequence: 1 givenname: Shih-Wei orcidid: 0000-0003-1343-0838 surname: Lin fullname: Lin, Shih-Wei organization: Department of Information Management, Chang Gung University, Taoyuan City, Taiwan – sequence: 2 givenname: Chung-Cheng surname: Lu fullname: Lu, Chung-Cheng organization: Department of Transportation and Logistics Management, National Chiao Tung University, Hsinchu, Taiwan – sequence: 3 givenname: Kuo-Ching orcidid: 0000-0002-9549-5290 surname: Ying fullname: Ying, Kuo-Ching email: kcying@ntut.edu.tw organization: Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan
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SubjectTerms	Algorithms cloud theory-based iterated greedy algorithm Computing time Flowcharts Greedy algorithms Heuristic methods Indexes Industries Job shop scheduling Job shops metaheuristics no-wait flowshop Particle swarm optimization Scheduling Single machine scheduling Urban areas
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Title	Minimizing the Sum of Makespan and Total Weighted Tardiness in a No-Wait Flowshop
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