Fuzzy Multi-objective Linear Programming Problems Sensitivity Analyses


Authors

M. Pattnaik - Dept. of Business Administration, Utkal University, Bhubaneswar-751004, India.


Abstract

Thanks to global competition, faster product development, and increasingly flexible manufacturing systems, an unprecedented number and variety of products are competing in markets ranging from apparel and toys to power tools and computers. The dramatic increase in demand unpredictability is fairly recent, 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 note, using the concept of comparison of fuzzy numbers, a very effective method is introduced 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 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’s ranking technique. The proposed procedure was programmed and the three dimensional mesh plot diagram is represented through MATLAB (R2009a) version software. The model is illustrated with numerical example and a sensitivity analyses are of the optimal solution is studied with respect to changes in parameter which incorporates all concepts of a fuzzy arithmetic approach to draw managerial insights.


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ISRP Style

M. Pattnaik, Fuzzy Multi-objective Linear Programming Problems Sensitivity Analyses, Journal of Mathematics and Computer Science, 7 (2013), no. 2, 131 - 137

AMA Style

Pattnaik M., Fuzzy Multi-objective Linear Programming Problems Sensitivity Analyses. J Math Comput SCI-JM. (2013); 7(2):131 - 137

Chicago/Turabian Style

Pattnaik, M.. "Fuzzy Multi-objective Linear Programming Problems Sensitivity Analyses." Journal of Mathematics and Computer Science, 7, no. 2 (2013): 131 - 137


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