New Heuristics to Stochastic Dynamic Lot Sizing Problem

Abstract

Simultaneous consideration of both demand and price uncertainties is not studied extensively in the literature.  This problem is mathematically intractable for cases where complex problem structure exists.  This study proposes new heuristics that consider demand and purchasing price uncertainties simultaneously. When all the costs are constant over time, this is the classical dynamic lot sizing problem for which the optimal solution can be obtained by the Wagner-Whitin algorithm. Purchasing decisions are made on a rolling horizon basis rather than fixed planning horizon. Well-known Least Unit Cost and Silver-Meal algorithms are modified for both time varying purchasing price and rolling horizon. The proposed heuristic is basically based on a cost-benefit evaluation at decision points. A numerical example is explained for showing how heuristics are working in detail. The aim of study is to enlighten about problem that is taken into account.

 

Key Words: Inventory; Stochastic lot sizing; Rolling horizon; Simulation.,

 

 

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Abstract

References

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