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Optimization of Inventory Model-Cost Parameters, Inventory and Lot Size as Fuzzy Numbers
R.Kasthuri1, P.Vasanthi2, S.Ranganayaki3

1Dr.R.Kasthuri*, Department of Mathematics, Sri Ramakrishna Engineering College, Coimbatore, India.
2Dr.P.Vasanthi, Department of Mathematics, Sri Ramakrishna Engineering College, Coimbatore, India.
3Dr.S.Ranganayaki, Department of Mathematics, Sri Ramakrishna Engineering College, Coimbatore, India
Manuscript received on October 05, 2020. | Revised Manuscript received on October 10, 2020. | Manuscript published on October 30, 2020. | PP: 365-369 | Volume-10 Issue-1, October 2020. | Retrieval Number:  100.1/ijeat.A18931010120 | DOI: 10.35940/ijeat.A1893.1010120
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© The Authors. 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 general, the demand rate and the unit cost of the items remains constant inspite of lot size in inventory models. But in reality, the demand rate and the unit cost of the items are connected together. In this research, demand dependent unit cost inventory model is considered where different cost parameters, maximum inventory and the lot size of the model are taken under fuzzy environment. First an analytic solution of the crisp model is obtained by the method of calculus where the inventory parameters are exact and deterministic. Later, the problem is developed with fuzzy parameters where inaccuracy has been introduced through triangular membership function.Then the defuzzification of the model is done by using the method of Graded mean integration. An optimal solution is obtained using Karush Kuhn-Tucker conditions approach. An illustrative model is done and an analysis of total cost for different measures of possibility are performed and tabulated. 
Keywords: Demand dependent on unit cost, Graded mean integration, Karush Kuhn-Tucker conditions technique, Triangular fuzzy number.