| Record number | 498406 |
|---|---|
| Title | A sample-based method for perishable good inventory control with a service level constraint |
| Author(s) | Hendrix, Eligius M.T.; Pauls-Worm, Karin G.J.; Rossi, Roberto; Alcoba, Alejandro G.; Haijema, Rene |
| Source | In: Computational Logistics. - Springer Verlag (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ) - ISBN 9783319242637 - p. 526 - 540. |
| Event | 6th International Conference on Computational Logistics, ICCL 2015, Delft, 2015-09-23/2015-09-25 |
| DOI | http://dx.doi.org/10.1007/978-3-319-24264-4_36 |
| Department(s) |
Operations Research and Logistics WASS Wageningen Business School |
| Publication type | Peer reviewed book chapter |
| Publication year | 2015 |
| Keyword(s) | Chance constraint - Inventory control - MINLP - Monte carlo - Perishable products |
| Abstract | This paper studies the computation of so-called order-upto levels for a stochastic programming inventory problem of a perishable product. Finding a solution is a challenge as the problem enhances a perishable product, fixed ordering cost and non-stationary stochastic demand with a service level constraint. An earlier study [7] derived order-up-to values via an MILP approximation. We consider a computational method based on the so-called Smoothed Monte Carlo method using sampled demand to optimize values. The resulting MINLP approach uses enumeration, bounding and iterative nonlinear optimization. |
| Comments |
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