Optimal Lot Size with Partial Backlogging Under the Occurrence of Imperfect Quality Items

Author(s):  
G. Karakatsoulis ◽  
K. Skouri
Author(s):  
Chandra K. Jaggi ◽  
Prerna Gautam ◽  
Aditi Khanna

In retail industries every ordered lot carry some fraction of imperfect quality items which can vary depending upon production and handling conditions. The situation is even more subtle when the items are prone to deterioration. However, an inspection process can spare us from such a criticality by bifurcating the defectives from the good quality lot. Thus, a screening process is mandatory. In the hyper-competitive market, trade-credit is well-known gimmick in order to boost the sales. Keeping in view, an inventory scenario of a retailer is investigated who has to deal with imperfect and “deteriorating items” under “permissible delay in payments”. The demand is assumed to be increasing exponentially. Shortages are permitted to occur and supposed to be “partially backlogged.” Rate of backlogging is assumed to have inverse relation with the waiting time for the subsequent replenishment. In this chapter, shortage point and length of cycle are jointly optimized. Numerical analysis and sensitivity analysis is performed to provide important insights for managerial persistence.


2007 ◽  
Vol 31 (10) ◽  
pp. 2149-2159 ◽  
Author(s):  
L.A. San-José ◽  
J. Sicilia ◽  
J. García-Laguna

Author(s):  
Arindum Mukhopadhyay ◽  
Adrijit Goswami

Imperfect quality Items are unavoidable in an Inventory system due to imperfect productionprocess, natural disasters, damages, or many other reasons. The setup cost and production cycletime can be related in terms of process deterioration and learning and forgetting effects. Learningreduces production run length and setup cost, whereas deterioration and forgetting increases both.Keeping these facts in mind, this paper investigates an Economic Production Quantity (EPQ) modelwith imperfect quality items with varying set-up costs. Mathematical model and solution proceduresare developed with major insight to its charecteristics. Numerical example and sensitivity analysisare provided to illustrate and analyze the model performance. It is observed that our model has asignificant impacts on the optimal lot size and optimal profit of the model.Classication: 90B05


2008 ◽  
Vol 191 (1) ◽  
pp. 127-141 ◽  
Author(s):  
Maw-Sheng Chern ◽  
Hui-Ling Yang ◽  
Jinn-Tsair Teng ◽  
Sotiris Papachristos

2011 ◽  
Vol 42 (8) ◽  
pp. 1409-1419 ◽  
Author(s):  
Monami Das Roy ◽  
Shib Sankar Sana ◽  
Kripasindhu Chaudhuri

2011 ◽  
Vol 42 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Tsu-Pang Hsieh ◽  
Mei-Chuan Cheng ◽  
Chung-Yuan Dye ◽  
Liang-Yuh Ouyang

Author(s):  
Leopoldo Eduardo Cárdenas-Barrón ◽  
Osman Albert Marquez-Rios ◽  
Irene Sánchez-Romero ◽  
Buddhadev Mandal

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