Heuristics for the stochastic economic lot sizing problem with remanufacturing under backordering costs
| Autor: | Huseyin Tunc, Onur A. Kilic |
|---|---|
| Přispěvatelé: | Research programme OPERA |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
Information Systems and Management General Computer Science Heuristic (computer science) Computer science 0211 other engineering and technologies Time horizon 02 engineering and technology Management Science and Operations Research Industrial and Manufacturing Engineering 0502 economics and business MANAGEMENT OPTIMIZATION Integer programming Remanufacturing Cost performance Inventory control 050210 logistics & transportation INVENTORY CONTROL 021103 operations research SCHEDULING PROBLEM Job shop scheduling 05 social sciences RETURNS Modeling and Simulation Convex optimization Heuristics |
| Zdroj: | European Journal of Operational Research, 276(3), 880-892. ELSEVIER SCIENCE BV |
| ISSN: | 0377-2217 |
| Popis: | We consider a production system where demand can be met by manufacturing new products and re manufacturing returned products, and address the economic lot sizing problem therein. The system faces stochastic and time-varying demands and returns over a finite planning horizon. The problem is to match supply with demand, while minimizing the total expected cost which is comprised of fixed production costs and inventory (holding and backordering) costs. We introduce heuristic policies for this problem which offer different levels of flexibility with respect to production decisions. We present computational methods for these policies based on convex optimization and certainty equivalent mixed integer programming, and numerically assess their cost performance and computational efficiency by means of simulation. (C) 2019 Elsevier B.V. All rights reserved. |
| Databáze: | OpenAIRE |
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