A NOTE ON LEAD TIME AND DISTRIBUTIONAL ASSUMPTIONS IN CONTINUOUS-REVIEW INVENTORY MODELS

Authors
Citation
I. Moon et S. Choi, A NOTE ON LEAD TIME AND DISTRIBUTIONAL ASSUMPTIONS IN CONTINUOUS-REVIEW INVENTORY MODELS, Computers & operations research, 25(11), 1998, pp. 1007-1012
Citations number
11
Categorie Soggetti
Operatione Research & Management Science","Computer Science Interdisciplinary Applications","Operatione Research & Management Science","Computer Science Interdisciplinary Applications","Engineering, Industrial
ISSN journal
03050548
Volume
25
Issue
11
Year of publication
1998
Pages
1007 - 1012
Database
ISI
SICI code
0305-0548(1998)25:11<1007:ANOLTA>2.0.ZU;2-#
Abstract
There is a rapidly growing literature on modelling the effects of inve stment strategies to control givens such as setup time, setup cost, qu ality level and lead time. Recently, a continuous review inventory mod el with a mixture of backorders and lost sales in which both lead time and the order quantity are decision variables has been studied. The o bjectives of this paper are twofold. Firstly, we want to correct and i mprove the recently studied model by simultaneously optimizing both th e order quantity and the reorder point. A significant amount of saving s over the model can be achieved. We illustrate these savings by solvi ng the same examples in the study. Secondly, we then develop a minimax distribution free procedure for the problem. Recently, there have bee n some studies on lead time reduction to provide more meaningful mathe matical models to decision makers. Ouyang et al. study a continuous re view inventory model in which lead time is a decision variable. Howeve r, their algorithm cannot find the optimal solution due to the flaws i n the modeling and the solution procedure. We present a complete proce dure to find the optimal solution for the model. In addition to the ab ove contribution, we also apply the minimax distribution free approach to the model to devise a practical procedure which can be used withou t specific information on demand distribution. (C) 1998 Elsevier Scien ce Ltd. All rights reserved..