Meta-heuristic algorithms for optimization of hybrid flowshop scheduling problems: A comprehensive review of the state of the art

Abstract

The hybrid flowshop scheduling problem (HFSP), which combines classical flowshop and parallel machine scheduling environments, has gained significant attention in recent years and has various application areas such as manufacturing, healthcare management, seaport operations, agricultural activities, and cloud computing. The HFSP considers multiple stages, at least one of them includes identical, uniform, or unrelated parallel machines, and aims to determine machine assignments and job sequences simultaneously at each stage. Since the HFSP has an NP-hard structure as a combinatorial optimization problem, exact methods like the branch & bound algorithm are not capable of obtaining promising solutions for large-sized problems within a reasonable time. At this point, meta-heuristic algorithms inspired by nature and based on mathematical concepts are effectively utilized to solve this type of complicated optimization problem. Therefore, in this paper, a state-of-the-art review on metaheuristics applied to solve HFSPs has been carried out using the Preferred Reporting Items for Systematic Re views and Meta-Analyses (PRISMA) methodology, which enables the realization of systematic reviews and metaanalyses in a specified research domain. As a result of the execution of this systematic review methodology, 328 articles published in a decade from 2015 to 2024 have been determined and these articles have been statistically and mathematically analyzed in terms of various characteristics such as year, country, journal, publisher, objective functions, meta-heuristic optimization methods, performance metrics, test instances, and parameter optimization techniques. The analysis results have been presented through charts and tables for visual demon stration with the aim of revealing the current state of the existing literature, recent developments, and future research suggestions related to meta-heuristic algorithms used to solve the HFSPs. Thus, it has been desired to provide a beneficial road map for researchers conducting research in this area.