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Joint energy capacity and production planning optimization in flow-shop systems
- 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.
- Subjects :
- Mathematical optimization
business.industry
Computer science
Applied Mathematics
Reliability (computer networking)
Probabilistic logic
Flow shop scheduling
Sizing
Renewable energy
Production planning
Modeling and Simulation
Programming paradigm
[INFO]Computer Science [cs]
business
Energy source
ComputingMilieux_MISCELLANEOUS
Subjects
Details
- ISSN :
- 0307904X
- Volume :
- 102
- Database :
- OpenAIRE
- Journal :
- Applied Mathematical Modelling
- Accession number :
- edsair.doi.dedup.....2ee3ed6cae2be337c38016c1a1b99370