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Decision Making Approach to Fuzzy Linear Programming (FLP) Problems with Post Optimal Analysis

Decision Making Approach to Fuzzy Linear Programming (FLP) Problems with Post Optimal Analysis

Monalisha Pattnaik
Copyright: © 2015 |Volume: 6 |Issue: 4 |Pages: 16
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781466678026|DOI: 10.4018/IJORIS.2015100105
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MLA

Pattnaik, Monalisha. "Decision Making Approach to Fuzzy Linear Programming (FLP) Problems with Post Optimal Analysis." IJORIS vol.6, no.4 2015: pp.75-90. http://doi.org/10.4018/IJORIS.2015100105

APA

Pattnaik, M. (2015). Decision Making Approach to Fuzzy Linear Programming (FLP) Problems with Post Optimal Analysis. International Journal of Operations Research and Information Systems (IJORIS), 6(4), 75-90. http://doi.org/10.4018/IJORIS.2015100105

Chicago

Pattnaik, Monalisha. "Decision Making Approach to Fuzzy Linear Programming (FLP) Problems with Post Optimal Analysis," International Journal of Operations Research and Information Systems (IJORIS) 6, no.4: 75-90. http://doi.org/10.4018/IJORIS.2015100105

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Abstract

This paper finds solutions to the fuzzy linear program where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi objective programming methods. Unfortunately all these methods have shortcomings. In this paper, using the concept of comparison of fuzzy numbers, the author introduces a very effective method for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the simplex based method. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a) version software, the four dimensional slice diagram is represented to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights.

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