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Optimal Policy for Non-Instantaneous Decaying Inventory Model with Learning Effect and Partial Shortages
Author(s) -
Anchal Agarwal,
Isha Sangal,
S. R.
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017913318
Subject(s) - economic shortage , computer science , policy learning , operations research , industrial engineering , machine learning , mathematics , philosophy , linguistics , government (linguistics) , engineering
Deterioration of goods and learning is a realistic phenomenon in daily life. Therefore maintaining the stock of decaying items becomes an important factor for decision makers. In this study deterioration rate follows the Weibull distribution and holding cost is gradually decreases, therefore learning effect is incorporated on holding cost. Many researchers generally assumed that the shortages are either completely backlogged or lost. But in this paper shortage is allowed and partial backlogged. The backlogging rate is taken as exponential function of time. Numerical examples are provided to further illustrate the model. Sensitivity analysis has been carried out to analyze the impact of change in various parameters. The aim of this model is to minimize the total cost.

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