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Joint energy capacity and production planning optimization in flow-shop systems

Authors :
Taha Arbaoui
Alice Yalaoui
Melek Rodoplu
Département Sciences de la Fabrication et Logistique (SFL-ENSMSE)
École des Mines de Saint-Étienne (Mines Saint-Étienne MSE)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-CMP-GC
Laboratoire d'Optimisation des Systèmes Industriels (LOSI)
Laboratoire Informatique et Société Numérique (LIST3N)
Université de Technologie de Troyes (UTT)-Université de Technologie de Troyes (UTT)
Source :
Applied Mathematical Modelling, Applied Mathematical Modelling, 2022, 102, pp.706-725. ⟨10.1016/j.apm.2021.09.036⟩
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

This study introduces new probabilistic constraints and objective functions to manage the uncertain nature of the renewable energy sources in single-item capacitated lot sizing problem for flow-shop configurations by integrating the capacity contract selection problem with multiple energy sources. The aim of the probabilistic models built by considering the different probabilistic constraints and objective functions is to provide a decision-making tool and to promote the use of renewable energy sources in manufacturing industry despite of their stochastic nature. Mixed Integer Non-Linear Programming models are proposed by integrating the uncertainty of the renewable energy sources based on different features. The developed models are tested on a small-size instance and the results of the models are compared in terms of economical, ecological and reliability aspects.

Details

ISSN :
0307904X
Volume :
102
Database :
OpenAIRE
Journal :
Applied Mathematical Modelling
Accession number :
edsair.doi.dedup.....2ee3ed6cae2be337c38016c1a1b99370