Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm

Abstract

AbstractThe multi-objective reentrant hybrid flowshop scheduling problem (RHFSP) exhibits significance in many industrial applications, but appears under-studied in the literature. In this study, an iterated Pareto greedy (IPG) algorithm is proposed to solve a RHFSP with the bi-objective of minimising makespan and total tardiness. The performance of the proposed IPG algorithm is evaluated by comparing its solutions to existing meta-heuristic algorithms on the same benchmark problem set. Experimental results show that the proposed IPG algorithm significantly outperforms the best available algorithms in terms of the convergence to optimal solutions, the diversity of solutions and the dominance of solutions. The statistical analysis manifestly shows that the proposed IPG algorithm can serve as a new benchmark approach for future research on this extremely challenging scheduling problem.Keywords: schedulingreentrant hybrid flowshopbi-objectivemeta-heuristic AcknowledgementThe authors would like to thank Professors Hang-Min Cho, Suk-Joo Bae, Jungwuk Kim and In-Jae Jeong (2011) for providing their benchmark problem set and solutions to us.FundingThis research was partially supported by the National Science Council of the Republic of China (Taiwan) [grant numbers NSC 102-2221-E-027-056 and NSC 101-2410-H-182-004-MY2].