EOQ Model with Permissible Delay in Payments under Fuzzy Environment

2014 ◽  
pp. 281-296
Author(s):  
Chandra K. Jaggi ◽  
Anuj Sharma ◽  
Reena Jain
Keyword(s):  
Cycle Length ◽  
Delay Period ◽  
Order Quantity ◽  
Distance Method ◽  
Permissible Delay In Payments ◽  
Signed Distance ◽  
Eoq Model ◽  
Fuzzy Environment ◽  
Delay In Payments ◽  
The Cost

This chapter introduces an economic order quantity inventory model under the condition of permissible delay in payments in fuzzy environment. All the parameters of the model, excluding permissible delay period and cycle length, are taken to be trapezoidal Fuzzy numbers. The arithmetic operations are defined under the function principle. The cost function has been defuzzified using signed distance method and thereby solved to obtain the optimal replenishment period. The numerical example is presented to show the validity of the model followed by sensitivity analysis.

Fuzzification of EOQ Model Under the Condition of Permissible Delay in Payments

2012 ◽  
Vol 3 (2) ◽  
pp. 1-19 ◽  
Author(s):  
Chandra K. Jaggi ◽  
Anuj Sharma ◽  
Reena Jain
Keyword(s):  
Fuzzy Numbers ◽  
Delay Period ◽  
Order Quantity ◽  
Distance Method ◽  
Permissible Delay In Payments ◽  
Signed Distance ◽  
Eoq Model ◽  
Fuzzy Environment ◽  
Delay In Payments ◽  
The Cost

This paper formulates an economic order quantity inventory model under the condition of permissible delay in payments in fuzzy environment. All the parameters of the model, excluding permissible delay period and cycle length, are taken to be trapezoidal Fuzzy numbers. The arithmetic operations are defined under the function principle. The cost function has been defuzzified using signed distance method and thereby solved to obtain the optimal replenishment period. The numerical example is presented to show the validity of the model followed by sensitivity analysis.

ECONOMIC ORDER QUANTITY UNDER CONDITIONS OF A ONE-TIME-ONLY EXTENDED PERMISSIBLE DELAY PERIOD IN PAYMENTS

2008 ◽  
Vol 25 (02) ◽  
pp. 267-277 ◽  
Author(s):  
SURESH KUMAR GOYAL ◽  
CHUN-TAO CHANG
Keyword(s):  
Business Environment ◽  
Delay Period ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Permissible Delay In Payments ◽  
Numerical Examples ◽  
Delay In Payments ◽  
Theoretical Results ◽  
Special Order

In today's business environment, a supplier usually offers customers a permissible delay for settling outstanding account balance for the goods supplied. However, a supplier on occasion may allow this permissible delay in payments to be more than the usual during a given specified period. In this paper, we establish an appropriate model for a customer to determine its optimal special order quantity when the supplier offers a special extended permissible delay for one time only during a specified period. We then establish two theorems for a customer to find the optimal special order quantity. Finally, several numerical examples are given to illustrate the theoretical results.

scholarly journals Retailer's EOQ Model with Limited Storage Space Under Partially Permissible Delay in Payments

2007 ◽  
Vol 2007 ◽  
pp. 1-18 ◽  
Author(s):  
Yung-Fu Huang ◽  
Chih-Sung Lai ◽  
Maw-Liann Shyu
Keyword(s):  
Lot Sizing ◽  
Cost Minimization ◽  
Optimal Order ◽  
Storage Space ◽  
Order Quantity ◽  
Permissible Delay In Payments ◽  
Eoq Model ◽  
Replenishment Policy ◽  
Cost Minimization Problem ◽  
Delay In Payments

The main purpose of this paper wants to investigate the optimal retailer's lot-sizing policy with two warehouses under partially permissible delay in payments within the economic order quantity (EOQ) framework. In this paper, we want to extend that fully permissible delay in payments to the supplier would offer the retailer partially permissible delay in payments. That is, the retailer must make a partial payment to the supplier when the order is received. Then the retailer must pay off the remaining balance at the end of the permissible delay period. In addition, we want to add the assumption that the retailer's storage space is limited. That is, the retailer will rent the warehouse to store these exceeding items when the order quantity is larger than retailer's storage space. Under these conditions, we model the retailer's inventory system as a cost minimization problem to determine the retailer's optimal cycle time and optimal order quantity. Three theorems are developed to efficiently determine the optimal replenishment policy for the retailer. Finally, numerical examples are given to illustrate these theorems and obtained a lot of managerial insights.

scholarly journals Inventory Model with Demand Dependant on Unit Cost- Input Parameters as Triangular Fuzzy Numbers

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
R. Kasthuri, Et. al.
Keyword(s):  
Fuzzy Numbers ◽  
Unit Cost ◽  
Inventory Model ◽  
Average Total Cost ◽  
Triangular Fuzzy Numbers ◽  
Lot Size ◽  
Distance Method ◽  
Total Cost ◽  
Signed Distance ◽  
Fuzzy Environment

This paper considers an inventory model in which the shortages are backlogged and the demand is dependent on unit cost. An optimum value for average total cost is calculated by considering various input costs, lot size and maximum inventory under fuzzy environment. The process of defuzzification is done by using the signed distance method. Numerical example and sensitivity analysis is given for calculating both crisp and fuzzy values of the total cost.

scholarly journals A Study of an EOQ Model under Lock Fuzzy Environment

Mathematics ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 75 ◽  
Author(s):  
Suman Maity ◽  
Sujit Kumar De ◽  
Sankar Prasad Mondal
Keyword(s):  
Inventory Management ◽  
Numerical Study ◽  
Management Problem ◽  
Final State ◽  
Eoq Model ◽  
Fuzzy Environment ◽  
Demand Rate ◽  
Computer Based ◽  
The Cost ◽  
Cost Vector

The present article was developed for the economic order quantity (EOQ) inventory model under daytime, non-random, uncertain demand. In any inventory management problem, several parameters are involved that are basically flexible in nature with the progress of time. This model can be split into three different sub-models, assuming the demand rate and the cost vector associated with the model are non-randomly uncertain (i.e., fuzzy), and these may include some of the retained learning experiences of the decision-maker (DM). However, the DM has the option of revising his/her decision through the application of the appropriate key vector of the fuzzy locks in their final state. The basic novelty of the present model is that it includes a computer-based decision‐making process involving flowchart algorithms that are able to identify and update the key vectors automatically. The numerical study indicates that when all parameters are assumed to be fuzzy, the double keys of the fuzzy lock provide a more accurate optimum than other methods. Sensitivity analysis and graphical illustrations are made for better justification of the model.

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