A comprehensive literature review of the flowshop group scheduling problems: systematic and bibliometric reviews

Abstract

AbstractThis paper deals with an overview of flowshop group scheduling problems in the manufacturing environment. The aim of this paper is twofold: (i) making a comprehensive survey of research on flowshop group scheduling problems in manufacturing systems, and (ii) presenting a bibliometric analysis. We address the general definition of flowshop group scheduling problems and provide a taxonomy of methodologies used in previous literature. The papers are presented from several perspectives, including the utilised objective functions, a transformation of problem structure, benchmarks in existing literature, and solution approaches. Additionally, bibliometric analysis, including keyword and journal analyses, is conducted for articles published between 1986 and 2022. Finally, suggestions for future developments are listed to further consolidate this area.Keywords: Flowshop group scheduling problembibliometric analysissystematic analysiscellular manufacturingVOSviewer Disclosure statementNo potential conflict of interest was reported by the author(s).Data Availability StatementData sharing is not applicable to this article as no new data were created or analysed in this study.Additional informationNotes on contributorsNilgün İnceNilgün İnce is a Ph.D. candidate at Department of Industrial Engineering, Sakarya University, Turkey. She obtained BS degree in industrial engineering from Kütahya Dumlupınar University and MS degree in manufacturing systems engineering and management from University of Warwick (WMG) in 2018. She is funded by Republic of Turkey Ministry of National Education during master studies and participated projects in automotive manufacturing in UK. Her research interests include optimisation, hyper-heuristics and scheduling. She currently works as a lecturer at Alanya Alaaddin Keykubat University.Derya DeliktaşDerya Deliktaş is an associate professor at Department of Industrial Engineering in Faculty of Engineering, Kütahya Dumlupınar University, Turkey. She received the B.S. degree in industrial engineering and Ph.D. degree in industrial engineering from Erciyes University and Sakarya University, respectively. She did her post-doctoral research as a researcher supported by Scientific and Technological Research Council of Turkey (TÜBİTAK) in Computer Science and Operational Research with the Computational Optimisation and Learning (COL) Lab in the School of Computer Science at the University of Nottingham (UoN) in UK. Her research interests and activities are scheduling problems, assembly line balancing problems, portfolio optimisation, artificial intelligence methods, multi-criteria decision making methods, and data mining.İhsan Hakan Selviİhsan Hakan Selvi is an associate professor in Information Systems Engineering Department at Sakarya University, Turkey. He received the B.S. and Ph.D.degrees in industrial engineering from Sakarya University. He has been at Missouri Science and Technology University as a guest researcher. He works as a project executive in manufacturing projects supported by Scientific and Technological Research Council of Turkey (TÜBİTAK). His research interests are smart manufacturing and service systems, information systems, deep learning, scheduling and optimisation. He is on the editorial board of Sakarya University Journal of Science and Artificial Intelligence Theory and Applications. He has several management roles at Sakarya University and currently works as an assistant director of Institute of Natural Sciences.