Single-Source, Single-Destination Coordination of EOQ Model for Perishable Products with Quantity Discounts Incorporating Partial/Full Truckload Policy under Fuzzy Environment

2012 ◽  
pp. 971-982 ◽  
Author(s):  
Sandhya Makkar ◽  
P. C. Jha ◽  
Nisha Arora
Keyword(s):  
Perishable Products ◽  
Quantity Discounts ◽  
Single Source ◽  
Eoq Model ◽  
Fuzzy Environment

Development of an EOQ Model for Single Source to Multi Destination

2012 ◽  
Vol 3 (4) ◽  
pp. 51-70
Author(s):  
Kanika Gandhi ◽  
P. C. Jha ◽  
M. Mathirajan
Keyword(s):  
Real Life ◽  
Fuzzy Optimization ◽  
Single Source ◽  
Short Life ◽  
Eoq Model ◽  
Industry Environment ◽  
Constant Quantity ◽  
Demand Rate ◽  
Holding Cost

Industry environment has become competitive because of product’s short life cycle. Competition reaches to extreme, when products are deteriorating which further makes demand uncertain. Generally, in deriving the solution of economic order quantity (EOQ) inventory model, the authors consider the demand rate as constant quantity. But in real life, demand cannot be forecasted precisely which causes fuzziness in related constraints and cost functions. Managing inventory, procurement, and transportation of deteriorating natured products with fuzzy demand, and holding cost at source and destination becomes very crucial in supply chain management (SCM). The objective of the current research is to develop a fuzzy optimization model for minimizing cost of holding, procurement, and transportation of goods from single source point to multi demand points with discount policies at the time of ordering and transporting goods in bulk quantity. A real life case study is produced to validate the model.

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.

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.

An EOQ model with quantity discounts for both purchasing price and freight cost

1990 ◽  
Vol 17 (1) ◽  
pp. 73-78 ◽  
Author(s):  
Hark Hwang ◽  
Dug Hee Moon ◽  
Seong Whan Shinn
Keyword(s):  
Quantity Discounts ◽  
Eoq Model

Study on EOQ model in the fuzzy environment

2004 ◽  
Author(s):  
Zhang Long ◽  
Song Shiji ◽  
Liu Lianchen ◽  
Wu Cheng
Keyword(s):  
Eoq Model ◽  
Fuzzy Environment

Deteriorating Inventory Model under Permissible Delay in Payments and Fuzzy Environment

2016 ◽  
pp. 77-99 ◽  
Author(s):  
Nita H. Shah ◽  
Sarla Pareek ◽  
Isha Sangal
Keyword(s):  
Solution Procedure ◽  
Inventory Model ◽  
Variable Cost ◽  
Selling Price ◽  
Gravity Method ◽  
Deterioration Rate ◽  
Eoq Model ◽  
Fuzzy Environment ◽  
Demand Rate ◽  
Delay In Payments

This paper deals with the problem of determining the EOQ model for deteriorating items in the fuzzy sense where delay in payments is permissible. The demand rate, ordering cost, selling price per item and deterioration rate are taken as fuzzy numbers. The total variable cost in fuzzy sense is de-fuzzified using the centre of gravity method. The solution procedure has been explained with the help of numerical example.

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.

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