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Kluwer Academic Publishers, , With B. Annals of Operations Research 85 Programming Ser. A 89 With D. Dentcheva, A. On convex probabilistic programming with discrete distributions. Nonlinear Analysis 47 Bounds for probabilistic integer programming. Discrete Applied Mathematics Operations Research Letters 32 With X.

Operations Research Letters 33 With H. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive Bellman equations. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. Mathematics Applications. Buy eBook. Buy Softcover. Table 5. Table 6. Table 7.

Table 8. Data set of monthly DPUTs of two pharmaceutical products. Fig 1. Table 9. Descriptive statistics of monthly DPUT for the pharmaceutical product. Table Fig 2. Evaluation of out-of-sample scenarios for the case study according to the mentioned performance indicator. Acknowledgments The authors thank the editors and reviewers for their constructive comments on an earlier version of this manuscript which resulted in this improved version.

References 1. Kogan K, Tell H. Production smoothing by balancing capacity utilization and advance orders.

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Journal of Business Logistics. View Article Google Scholar 2. The impact of inventory management on stock-outs of essential drugs in Sub-Saharan Africa: secondary analysis of a field experiment in Zambia. Jing F, Lan Z. Forecast horizon of multi-item dynamic lot size model with perishable inventory.

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Tersine RJ. Principles of Inventory and Materials Management. Harris FW. How many parts to make at once. Factory, the Magazine of Management. View Article Google Scholar 6. Hillier F, Lieberman G. Introduction to Operational Research. Dynamic version of the economic lot size model. Management Science. View Article Google Scholar 8. Inventory management for new products with triangularly distributed demand and lead-time.

Computers and Operations Research. View Article Google Scholar 9. Karlin S. Dynamic inventory policy with varying stochastic demands. View Article Google Scholar Evans JR. An efficient implementation of the Wagner-Whitin algorithm for dynamic lot-sizing. Journal of Operations Management. Pochet Y, Wolsey LA. Lot-size models with backlogging: strong reformulations and cutting planes. Mathematical Programming. Lectures on Stochastic Programming: Modeling and Theory.

Robust optimization of large-scale systems.

Operations Research. Raa B, Aghezzaf H. A robust dynamic planning strategy for lot-sizing problems with stochastic demands. Journal of Intelligent Manufacturing. Dynamic programming and heuristic for stochastic uncapacitated lot-sizing problems with incremental quantity discount. Mathematical Problems in Engineering. Zhou Z, Guan Y. Two-stage stochastic lot-sizing problem under cost uncertainty.

Annals of Operations Research. Distributionally robust optimization of two-stage lot-sizing problems. Production and Operations Management. Single-item dynamic lot-sizing problems: An updated survey. European Journal of Operational Research. Orlicky JA.

Solving nonlinear stochastic optimization and equilibrium problems backwards

A review of techniques for buffering against uncertainty with MRP systems. Production Planning and Control. International Journal of Production Economics. Li H, Meissner J. Capacitated dynamic lot sizing with capacity acquisition. International Journal of Production Research.

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Static-dynamic uncertainty strategy for a single-item stochastic inventory control problem. Louly MA, Dolgui A. Optimal MRP parameters for a single item inventory with random replenishment lead time, POQ policy and service level constraint. A heuristic solution procedure for the dynamic lot sizing problem with remanufacturing and product recovery. A reformulation for the stochastic lot sizing problem with service-level constraints. Operations Research Letters. Tempelmeier H, Hilger T. Linear programming models for a stochastic dynamic capacitated lot sizing problem.

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Time-dependent demand in requirements planning: an exploratory assessment of the effects of serially correlated demand sequences on lot-sizing performance. Homem-de Mello T, Bayraksan G. Monte Carlo sampling-based methods for stochastic optimization. Surveys in Operations Research and Management Science. Simulation and optimization approaches to scenario tree generation. Journal of Economic Dynamics and Control. Rojas F, Leiva V. Inventory management in food companies with demand statistically dependent. Dunn P, Smyth G. Randomized quantile residuals. Journal of Computational and Graphical Statistics.

Stasinopoulos D, Rigby R. Journal of Statistical Software. Infanger G, Morton DP. Cut sharing for multistage stochastic linear programs with interstage dependency. Birge JR, Louveaux F. Introduction to Stochastic Programming. New York, US: Springer; Scenarios for multistage stochastic programs. Jain AK. Data clustering: 50 years beyond K-means. Pattern recognition letters. Journal of Classification. Brandimarte P. Multi-item capacitated lot-sizing with demand uncertainty.