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Advances in Fuzzy Systems
Volume 2016, Article ID 6132768, 10 pages
Research Article

A Novel Method for Optimal Solution of Fuzzy Chance Constraint Single-Period Inventory Model

Department of Mathematics, ITER, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha 751030, India

Received 16 July 2016; Accepted 11 October 2016

Academic Editor: Erich Peter Klement

Copyright © 2016 Anuradha Sahoo and J. K. Dash. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A method is proposed for solving single-period inventory fuzzy probabilistic model (SPIFPM) with fuzzy demand and fuzzy storage space under a chance constraint. Our objective is to maximize the total profit for both overstock and understock situations, where the demand for each product in the objective function is considered as a fuzzy random variable (FRV) and with the available storage space area , which is also a FRV under normal distribution and exponential distribution. Initially we used the weighted sum method to consider both overstock and understock situations. Then the fuzziness of the model is removed by ranking function method and the randomness of the model is removed by chance constrained programming problem, which is a deterministic nonlinear programming problem (NLPP) model. Finally this NLPP is solved by using LINGO software. To validate and to demonstrate the results of the proposed model, numerical examples are given.