On the Multi-Resource Flexible Job-Shop Scheduling Problem with Arbitrary Precedence Graphs
Kasapidis, G. A., Dauzère-Pérèz, S., Paraskevopoulos, D. C. ORCID: 0000-0002-7004-3263 , Repoussis, P. P. & Tarantilis, C. D. (2023). On the Multi-Resource Flexible Job-Shop Scheduling Problem with Arbitrary Precedence Graphs. Production and Operations Management, 32(7), pp. 2322-2330. doi: 10.1111/poms.13977
Abstract
This paper aims at linking the work presented in Dauz`ere-P´er`es et al. (1998) and more recently in Kasapidis et al. (2021) on the multi-resource flexible job-shop scheduling problem with non-linear routes or equivalently with arbitrary precedence graphs. In particular, we present a Mixed Integer Linear Programming model and a Constraint Programming model, to formulate the problem. We also compare the theorems introduced in Dauz`ere-P´er`es et al. (1998) and Kasapidis et al. (2021), and propose a new theorem extension. Computational experiments were conducted to assess the efficiency and effectiveness of all propositions. Lastly, the proposed MIP and CP models are tested on benchmark problems of the literature and comparisons are made with state-of-the-art algorithms.
Publication Type: | Article |
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Additional Information: | © 2023 The Authors. Production and Operations Management published by Wiley Periodicals LLC on behalf of Production and Operations Management Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
Publisher Keywords: | Flexible Job shop scheduling, multiple resources, integer linear programming, constraint programming, non-linear precedence constraints, arbitrary precedence graphs |
Subjects: | H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management |
Departments: | Bayes Business School > Management |
SWORD Depositor: |
Available under License Creative Commons Attribution Non-commercial.
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