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Stochastic program for disassembly lot-sizing under uncertain component refurbishing lead times
- Source :
- European Journal of Operational Research, European Journal of Operational Research, 2022, ⟨10.1016/j.ejor.2022.03.025⟩
- Publication Year :
- 2022
- Publisher :
- HAL CCSD, 2022.
-
Abstract
- International audience; Planning disassembly operations for a given demand in components is challenging in practice because the quality of recovered components is very uncertain, and thus the duration of refurbishing operations is unpredictable. In this paper, we address the capacitated disassembly lot-sizing problems under uncertain refurbishing durations. More precisely, we consider a two-level disassembly system with a single type of end-of-life product, a dynamic demand, and stochastic refurbishing lead times for all components. To deal with the static decision frameworks, this problem is modeled as a two-stage stochastic Mixed-Integer Linear Program (MILP), where the objective is to minimize the expected total cost. To alleviate the scalability issues, we propose a reformulation of the inventory constraint that significantly reduces the number of scenarios. In addition, to solve large scale problems, we couple this reformulation with Monte-Carlo sampling. We provide a rolling horizon approach to deal with the static decision framework, where disassembly decisions are updated when new information unfolds. Experimental results show the effectiveness of the proposed models and the convergence of the resulting Sample Average Approximation (SAA) estimator.
- Subjects :
- Information Systems and Management
Combinatorial optimization
General Computer Science
Modeling and Simulation
Monte-Carlo sampling
Stochastic programming
[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]
Management Science and Operations Research
Rolling horizon strategy
Industrial and Manufacturing Engineering
Capacitated disassembly lot-sizing
Stochastic refurbishing lead time
Subjects
Details
- Language :
- English
- ISSN :
- 03772217 and 18726860
- Database :
- OpenAIRE
- Journal :
- European Journal of Operational Research, European Journal of Operational Research, 2022, ⟨10.1016/j.ejor.2022.03.025⟩
- Accession number :
- edsair.doi.dedup.....e4555d9042644e5a2444e71fb3543f4a