Computational algorithmic procedure of optimal inventory policy involving a negative exponential crashing cost and variable lead time demand

2007 ◽  
Vol 184 (2) ◽  
pp. 798-808 ◽  
Author(s):  
Jong-Wuu Wu ◽  
Wen-Chuan Lee ◽  
Hui-Yin Tsai
Keyword(s):  
Lead Time ◽  
Inventory Policy ◽  
Crashing Cost ◽  
Negative Exponential ◽  
Algorithmic Procedure

scholarly journals Optimal Inventory Policy Involving Ordering Cost Reduction, Back-Order Discounts, and Variable Lead Time Demand by Minimax Criterion

2009 ◽  
Vol 2009 ◽  
pp. 1-19 ◽  
Author(s):  
Jong-Wuu Wu ◽  
Wen-Chuan Lee ◽  
Chia-Ling Lei
Keyword(s):  
Cost Reduction ◽  
Lead Time ◽  
Control Variable ◽  
Decision Variable ◽  
Minimax Criterion ◽  
Inventory Policy ◽  
Price Discounts ◽  
Ordering Cost Reduction ◽  
Back Order ◽  
Algorithmic Procedure

This paper allows the backorder rate as a control variable to widen applications of a continuous review inventory model. Moreover, we also consider the backorder rate that is proposed by combining Ouyang and Chuang (2001) (or Lee (2005)) with Pan and Hsiao (2001) to present a new form. Thus, the backorder rate is dependent on the amount of shortages and backorder price discounts. Besides, we also treat the ordering cost as a decision variable. Hence, we develop an algorithmic procedure to find the optimal inventory policy by minimax criterion. Finally, a numerical example is also given to illustrate the results.

scholarly journals Three-Echelon Inventory Model with Permissible Delay in Payments under Controllable Lead Time and Backorder Consideration

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
M. F. Yang ◽  
Wei-Chung Tseng
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Critical Issue ◽  
Solution Procedure ◽  
Inventory Model ◽  
Permissible Delay In Payments ◽  
Inventory Policy ◽  
Controllable Lead Time ◽  
Key Factor ◽  
Delay In Payments

This paper proposes a three-echelon inventory model with permissible delay in payments under controllable lead time and backorder consideration to find out the suitable inventory policy to enhance profit of the supply chain. In today’s highly competitive market, the supply chain management has become a critical issue in both practice and academic and supply chain members have to cooperate with each other to bring more benefits. In addition, the inventory policy is a key factor to influence the performance of the supply chain. Therefore, in this paper, we develop a three-echelon inventory model with permissible delay in payments under controllable lead time and backorder consideration. Furthermore, the purpose of this paper is to maximize the joint expect total profit on inventory model and attempt to discuss the inventory policy under different conditions. Finally, with a numerical example provided here to illustrate the solution procedure, we may discover that decision-makers can control lead time and payment time to enhance the performance of the supply chain.

scholarly journals Inventory model for deteriorating items with negative exponential demand, probabilistic deterioration and fuzzy lead time under partial back logging

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Nabendu Sen ◽  
Sumit Saha
Keyword(s):  
Inventory Management ◽  
Lead Time ◽  
Probability Distributions ◽  
Optimal Strategies ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Optimal Time ◽  
Inventory Cost ◽  
Total Inventory ◽  
Negative Exponential

The effect of lead time plays an important role in inventory management. It is also important to study the optimal strategies when the lead time is not precisely known to the decision makers. The aim of this paper is to examine the inventory model for deteriorating items with fuzzy lead time, negative exponential demand, and partially backlogged shortages. This model is unique in its nature due to probabilistic deterioration along with fuzzy lead time. The fuzzy lead time is assumed to be triangular, parabolic, trapezoidal numbers and the graded mean integration representation method is used for the defuzzification purpose. Moreover, three different types of probability distributions, namely uniform, triangular and Beta are used for rate of deterioration to find optimal time and associated total inventory cost. The developed model is validated numerically and values of optimal time and total inventory cost are given in tabular form, corresponding to different probability distribution and fuzzy lead-time. The sensitivity analysis is performed on variation of key parameters to observe its effect on the developed model. Graphical representations are also given in support of derived optimal inventory cost vs. time.

scholarly journals Data-Driven Iron and Steel Inventory Control Policies

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 718
Author(s):  
Tseng ◽  
Yu
Keyword(s):  
Markov Decision Process ◽  
Decision Process ◽  
Lead Time ◽  
Data Driven ◽  
Inventory Policy ◽  
Iron And Steel ◽  
Markov Decision ◽  
The Face ◽  
Optimal Material ◽  
In Transit

In this study, we investigated the optimal material inventory policy with regard to the iron and steel industry’s effort to reduce massive overstocking issues in the face of increased corporate competitiveness. We gathered actual data, including sales and inventory numbers, from a steel and iron company over a period of 216 weeks between January 2010 and February 2014. We then utilized the Markov decision process (MDP) to analyze this data for inventory problems, such as relevant reorder points and reorder quantity issues as they relate to lead time, stock on hand and the limitations of having stock in-transit. The purpose of the study was to determine the most effective method for minimizing costs by using the optimal inventory policy to calculate and verify the effectiveness of the results. The final 52 weeks of data were put aside, while the initial 164 weeks were used to create an inbound material receipt system to ultimately establish a yearly (52-week) policy based on the inventory and sales data for weeks 113–164. Finally, we verified the effectiveness of the policy using the data from the final 52 weeks. The results showed that our proposed categorization method was effective for reducing the quantity of inventory while still meeting quarterly demands.

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