Article ID: | iaor20101896 |
Volume: | 30 |
Issue: | 5 |
Start Page Number: | 869 |
End Page Number: | 886 |
Publication Date: | Sep 2009 |
Journal: | Journal of Information & Optimization Sciences |
Authors: | Tsao Yu-Chung |
Consider a continuous review inventory system with probabilistic demand under advance sales discount, partial backlogging and two-echelon trade credits. The objective is to determine the optimal ordering quantity and reorder point while minimizes the expected annual cost. The main purpose of this research is to relax several assumptions of traditional inventory models to cope with more general and practical situations. The methodology is illustrated on a real application where we predict a 2.5% decrease in a product cost if our model solution is implemented. Also, we discuss the influences of main system parameters on decisions in computational analysis