An improved particle swarm optimization algorithm to solve hybrid flowshop scheduling problems with the effect of human factors – A case study

•An improved particle swarm optimization algorithm is proposed to solve the hybrid flow shop scheduling problems to minimize the weighted sum of makespan and total flow time.•The skill factor, age factor, the learning and forgetting factors are considered.•Computational results reveal the effectiven...

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Bibliographic Details
Published in:	Computers & operations research Vol. 114; p. 104812
Main Authors:	Marichelvam, M.K., Geetha, M., Tosun, Ömür
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 01.02.2020 Pergamon Press Inc
Subjects:	Algorithms Computing time Flow time Human factors Hybrid flowshop Job shops Makespan NP-hard Operations research Particle swarm optimization Production scheduling Scheduling Variable neighbourhood search NP-hard Makespan Variable neighbourhood search Flow time Particle swarm optimization Hybrid flowshop
ISSN:	0305-0548, 1873-765X, 0305-0548
Online Access:	Get full text
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