A hybrid metaheuristic approach for minimizing the total flow time in a flow shop sequence dependent group scheduling problem
type: Item
instance of: scholarly article
title: A hybrid metaheuristic approach for minimizing the total flow time in a flow shop sequence dependent group scheduling problem
zbMATH Open document ID: 1461.90042
author: Xianqiang Yang
published in: Algorithms
publication date: 2019-03-26T00:00:00Z
review text: Summary: Production processes in Cellular Manufacturing Systems (CMS) often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS) problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS) problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs) and Biased Random Sampling (BRS) search techniques with the aim of minimizing the total flow time, \textit{i.e.}, the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation.
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 7042212
zbMATH Keywords: cellular manufacturing
zbMATH Keywords: genetic algorithm
zbMATH Keywords: encoding
zbMATH Keywords: decoding
zbMATH Keywords: sequencing
describes a project that uses: Genocop
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a7030376
OpenAlex ID: W2123087625
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DOI: 10.3390/A7030376
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description: scientific article; zbMATH DE number 7042212