A variable block insertion heuristic for permutation flowshops with makespan criterion

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Date

2017

Authors

M. Fatih Tasgetiren
Quan-Ke Pan
Damla Kizilay
Mario C. Velez-Gallego

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IEEE

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Green Open Access

Yes

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Abstract

This paper proposes a populated variable block insertion heuristic (PVBIH) algorithm for solving the permutation flowshop scheduling problem with the makespan criterion. The PVBIH algorithm starts with a minimum block size being equal to one. It removes a block from the current solution and inserts it into the partial solution randomly with a predetermined move size. A local search is applied to the solution found after several block moves. If the new solution generated after the local search is better than the current solution it replaces the current solution. It retains the same block size as long as it improves. Otherwise the block size is incremented by one and a simulated annealing-type of acceptance criterion is used to accept the new solution. This process is repeated until the block size reaches at the maximum block size. In addition we present a randomized profile fitting heuristic with excellent results. Extensive computational results on the Taillard's well-known benchmark suite show that the proposed PVBIH algorithm substantially outperforms the differential evolution algorithm (NS-SGDE) recently proposed in the literature.

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Keywords

Variable block insertion heuristic, flowshop scheduling, heuristic optimization, local search, randomized profile fitting heuristic, DIFFERENTIAL EVOLUTION ALGORITHM, BEE COLONY ALGORITHM, TOTAL WEIGHTED TARDINESS, PARTICLE SWARM OPTIMIZATION, ITERATED LOCAL SEARCH, FLOW-SHOP PROBLEM, DEPENDENT SETUP TIMES, SCHEDULING PROBLEM, GENETIC ALGORITHM, SINGLE-MACHINE, Flowshop Scheduling, Randomized Profile Fitting Heuristic, Local Search, Variable Block Insertion Heuristic, Heuristic Optimization, Randomized profile fitting heuristic, Heuristic optimization, Local search, Flowshop scheduling, Variable block insertion heuristic

Fields of Science

0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

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3

Source

IEEE Congress on Evolutionary Computation (CEC)

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Issue

Start Page

726

End Page

733
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CrossRef : 3

Scopus : 11

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11

checked on Apr 09, 2026

Web of Science™ Citations

7

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