A Robust Two-Machine Flow-Shop Scheduling Model with Scenario-Dependent Processing Times

Autor: Chia-Lun Hsu, Win-Chin Lin, Lini Duan, Jan-Ray Liao, Chin-Chia Wu, Juin-Han Chen
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Discrete Dynamics in Nature and Society, Vol 2020 (2020)
Druh dokumentu: article
ISSN: 1026-0226
1607-887X
08512140
DOI: 10.1155/2020/3530701
Popis: In many scheduling studies, researchers consider the processing times of jobs as constant numbers. This assumption sometimes is at odds with practical manufacturing process due to several sources of uncertainties arising from real-life situations. Examples are the changing working environments, machine breakdowns, tool quality variations and unavailability, and so on. In light of the phenomenon of scenario-dependent processing times existing in many applications, this paper proposes to incorporate scenario-dependent processing times into a two-machine flow-shop environment with the objective of minimizing the total completion time. The problem under consideration is never explored. To solve it, we first derive a lower bound and two optimality properties to enhance the searching efficiency of a branch-and-bound method. Then, we propose 12 simple heuristics and their corresponding counterparts improved by a pairwise interchange method. Furthermore, we set proposed 12 simple heuristics as the 12 initial seeds to design 12 variants of a cloud theory-based simulated annealing (CSA) algorithm. Finally, we conduct simulations and report the performances of the proposed branch-and-bound method, the 12 heuristics, and the 12 variants of CSA algorithm.
Databáze: Directory of Open Access Journals
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