Hybrid LS-SA-PS methods for solving fuzzy non-linear programming problems

Vasant, P. (2013) Hybrid LS-SA-PS methods for solving fuzzy non-linear programming problems. Mathematical and Computer Modelling, 57 (1-2). pp. 180-188. ISSN 08957177

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Abstract

The fuzzy optimization problem is one of the prominent topics in the broad area of artificial intelligence. It is applicable in the field of non-linear fuzzy programming. Its application as well as practical realization can been seen in all the real world problems. In this paper a large scale non-linear fuzzy programming problem was solved by hybrid optimization techniques like Line Search (LS), Simulated Annealing (SA) and Pattern Search (PS). An industrial production planning problem with a cubic objective function, eight decision variables and 29 constraints was solved successfully using the LS-SA-PS hybrid optimization techniques. The computational results for the objective function with respect to vagueness factor and level of satisfaction has been provided in the form of 2D and 3D plots. The outcome is very promising and strongly suggests that the hybrid LS-SA-PS algorithm is very efficient and productive in solving the large scale non-linear fuzzy programming problem. © 2011 Elsevier Ltd.

Item Type: Article
Additional Information: cited By 37
Uncontrolled Keywords: Fuzzy programming; Level of satisfaction; Line searches; Pattern search; Vagueness factor, Artificial intelligence; Simulated annealing, Fuzzy systems
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:52
Last Modified: 09 Nov 2023 15:52
URI: https://khub.utp.edu.my/scholars/id/eprint/4066

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