Rifai, Achmad Pratama and Mara, Setyo Tri Windras and Sudiarso, Andi (2021) Multi-objective distributed reentrant permutation flow shop scheduling with sequence-dependent setup time. EXPERT SYSTEMS WITH APPLICATIONS, 183. ISSN 0957-4174
Full text not available from this repository. (Request a copy)Abstract
The distributed reentrant permutation flow shop (DRPFS) is a combination of the reentrant flow shop problem and distributed scheduling. The DRPFS is a NP-hard problem that consists of two subproblems: (1) assigning a set of jobs to a set of available factories and (2) determining the operation sequence of jobs in each factory. This paper is the first study to consider the inclusion of sequence-dependent setup time in the DRPFS. The industrial applications of flow shop indicate that the machine setup time to process a job may depend on the previously processed jobs. Particularly, in DRPFS, the effect of sequence-dependent setup time is intensified due to its reentrant characteristic. An improved version of the multi-objective adaptive large neighborhood search (MOALNS) is proposed as a solution method for the sequence-dependent DRPFS with the aim to minimize the makespan, production cost, and tardiness. The proposed algorithm enhances the standard MOALNS by embedding an improved solution acceptance and non-dominated set updating criteria to assist the algorithm in finding the near-optimal Pareto front of the factory allocation and scheduling problems. To address the multiple objectives and the issue of non-uniform setup time, a new set of destroy and repair heuristics are developed. Further, the numerical experiments demonstrate the efficiency of IMOALNS in finding high-quality solutions in a relatively short time.
Item Type: | Article |
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Uncontrolled Keywords: | Multi-objective scheduling; Distributed manufacturing; Reentrant flow shop; Sequence-dependent setup time; Improved adaptive large neighborhood search |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Faculty of Engineering > Mechanical and Industrial Engineering Department |
Depositing User: | Sri JUNANDI |
Date Deposited: | 22 Oct 2024 06:28 |
Last Modified: | 22 Oct 2024 06:28 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/8981 |