Heuristics for the stochastic economic lot sizing problem with remanufacturing under backordering costs

• Published in: European journal of operational research Vol. 276; no. 3; pp. 880 - 892
• Main Authors: Kilic, Onur A., Tunc, Huseyin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-08-2019
• Subjects: Heuristic; Inventory; Mixed integer programming; Remanufacturing; Stochastic lot-sizing; Mixed integer programming; Remanufacturing; Stochastic lot-sizing; Inventory; Heuristic
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2019.01.051

•The stochastic economic lot sizing problem with remanufacturing is addressed.•Heuristic policies which offer different levels of flexibility are proposed.•Mathematical models are developed to obtain the parameters of heuristic policies.•Cost and computational performance of the proposed heuristics are compared in an extensive numerical study.
We consider a production system where demand can be met by manufacturing new products and remanufacturing 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.