Heuristic methods for the capacitated stochastic lot-sizing problem under the static-dynamic uncertainty strategy

Date

2019-09-01

Author

Randa, A. Cem
Dogru, Mustafa K.
İyigün, Cem
Ozen, Ulas

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We consider a lot-sizing problem in a single-item single-stage production system facing non-stationary stochastic demand in a finite planning horizon. Motivated by common practice, the set-up times need to be determined and frozen once and for all at the beginning of the horizon while decisions on the exact lot sizes can be deferred until the setup epochs. This operating scheme is referred to as the static dynamic uncertainty strategy in the literature. It has been shown that a modified base stock policy is optimal for a capacitated system with minimum lot size restrictions under the static-dynamic uncertainty strategy. However, the optimal policy parameters require an exhaustive search, for which the computational time grows exponentially in the number of periods in the planning horizon. In order to alleviate the computational burden for real-life size problems, we developed and tested seven different heuristics for computational efficiency and solution quality. Our extensive numerical experiments showed that average optimality gaps less than 0.1% and maximum optimality gaps below 4% can be attained in reasonable running times by using a combination of these heuristics. (C) 2019 Published by Elsevier Ltd.

Subject Keywords

Management Science and Operations Research, Modelling and Simulation, General Computer Science

URI

https://hdl.handle.net/11511/34338

Journal

COMPUTERS & OPERATIONS RESEARCH

DOI

https://doi.org/10.1016/j.cor.2019.03.007

Collections

Department of Industrial Engineering, Article

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Citation Formats

A. C. Randa, M. K. Dogru, C. İyigün, and U. Ozen, “Heuristic methods for the capacitated stochastic lot-sizing problem under the static-dynamic uncertainty strategy,” COMPUTERS & OPERATIONS RESEARCH, pp. 89–101, 2019, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34338.