A Fuzzy Based Two Warehouses Inventory Model for Deteriorating Items
A. K. Malik1, Yashveer Singh2, S. K. Gupta3

1A. K. Malik, Department of Mathematics, B.K. Birla Institute of Engineering &Technology, Pilani, Rajasthan (India.
2Yashveer Singh, Department of Computer Science, GRD Institute of Management & Technology, Dehradun, Uttarakhand, (India).
3S. K. Gupta, Department of Mathematics, D. N. College, Meerut, Uttar Pradesh (India).

Manuscript received on April 15, 2012. | Revised Manuscript received on April 20, 2012. | Manuscript published on May 05, 2012. | PP: 188-192 | Volume-2 Issue-2, May 2012 . | Retrieval Number: B0545042212/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In real life situations, especially for new products, the probability is not known due to lack of historical data and adequate information. Then these parameters and variables are treated as fuzzy parameters. Fuzzy set theory is now applied to problems in engineering, business, medical and related health sciences and natural sciences. Over the years there have been successful applications and implementations of fuzzy set theory in production management. In this study, a fuzzy based two warehouses inventory model has been developed with exponential demand. Deterioration rates of two warehouses are considered to be different due to change in environment. The holding cost in RW is assumed to be higher than those in OW. To reduce the inventory costs, it will be economical for firms to store goods in OW before RW, but clear the stocks in RW before OW. The parameters such as holding costs, ordering cost and deteriorating cost for two warehouses are considered as fuzzy number. We considered the triangular fuzzy number to represents the fuzzy parameters. The total inventory cost is obtained in crisp environment as well as fuzzy sense with the help of Signed distance method.

Keywords: Exponential demand, linear deterioration, Fuzzy model, Crisp model, Signed distance.