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pp.98-108
This paper introduces the existence of purchase dependence that was identified during the analysis of inventory operations practice at a sales agency of dealing with spare parts for ship engines and generators. Purchase dependence is an important factor in designing an inventory replenishment policy. However, it has remained mostly unaddressed. Purchase dependence is different from demand dependence. Purchase dependence deals with the purchase behavior of customers, whereas demand dependence deals with the relationship between item-demands. In order to deal with purchase dependence in inventory operations practice, this paper proposes (Q, r) models with the consideration of purchase dependence. Through a computer simulation experiment, this paper compares performance of the proposed (Q, r) models to that of a (Q, r) model ignoring purchase dependence. The simulation experiment is conducted for two cases : a case of using a lost sale cost and a case of using a service level. For a case of using a lost sale cost, this paper calculates an order quantity, Q and a reorder point, r using the iterative procedure. However, for a case of using a service level, it is not an easy task to find Q and r. The complexity stems from the interactions among inventory replenishment policies for items. Thus, this paper considers the genetic algorithm (GA) as an optimization method. The simulation results demonstrates that the proposed (Q, r) models incur less inventory operations cost (satisfies better service levels) than a (Q, r) model ignoring purchase dependence. As a result, the simulation results supports that it is important to consider purchase dependence in the inventory operations practice.
2. Model Formulation
2.1 An Existing (Q, r ) Model
2.2 The Proposed (Q, r ) Models
3. Simulation Experiment
3.1 A Case of using a Lost Sale Cost
3.2 A Case of using a Service Level
3.3 Findings
4. Conclusion
References
