A bi-objective re-entrant permutation flow shop scheduling problem: minimizing the makespan and maximum tardiness

Maedeh Fasihi (), Reza Tavakkoli-Moghaddam () and Fariborz Jolai ()
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Maedeh Fasihi: University of Tehran
Reza Tavakkoli-Moghaddam: University of Tehran
Fariborz Jolai: University of Tehran

Operational Research, 2023, vol. 23, issue 2, No 7, 41 pages

Abstract: Abstract This paper addresses a re-entrant permutation flow shop (RPFS) scheduling problem that minimizes the makespan and maximum tardiness of jobs and presents a two-step procedure. In the first step, a population is broken down into sub-populations, in which a genetic algorithm (GA) is applied to obtain an appropriate approximation of a Pareto front. In the second step, non-dominant solutions are unified as a single large population to enhance the Pareto-front. A multi-objective hybrid meta-heuristic algorithm is proposed based on a dominance relation. In general, proper combinations of multi-objective approaches are considered in two steps that combine elements of both GA and simulated annealing (SA). A hybrid meta-heuristic algorithm is used for raising the generality level. Thus, the same solution approach can be applied to various problems. The hybrid meta-heuristic algorithm is considered with Lorenz dominance and Pareto dominance separately. Three approaches are used to assess non-dominated solution sets. Afterward, a comparison between non-dominated sets taken from each step and non-dominated sorting genetic algorithm (NSGA-II) and Lorenz NSGA-II (LNSGA-II) algorithms proposed in the previous studies is carried out. The two-step algorithm is an effective method for this study, according to the computational research findings. Moreover, applying the set coverage criterion shows the superiority of Lorenz dominance over Pareto dominance relations.

Keywords: Re-entrant permutation flow shop scheduling; Lorenz dominance; Hybrid meta-heuristic; Pareto dominance (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12351-023-00770-0

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