Improved tabu search recursive fuzzy method for crude oil industry

Vasant, P. and Ganesan, T. and Elamvazuthi, I. (2012) Improved tabu search recursive fuzzy method for crude oil industry. International Journal of Modeling, Simulation, and Scientific Computing, 3 (1). ISSN 17939623

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Abstract

The minimization of the profit function with respect to the decision variables is very important for the decision makers in the oil field industry. In this paper, a novel approach of the improved tabu search algorithm has been employed to solve a large scale problem in the crude oil refinery industry. This problem involves 44 variables, 36 constraints, and four decision variables which represent four types of crude oil types. The decision variables have been modeled in the form of fuzzy linear programming problem. The vagueness factor in the decision variables is captured by the nonlinear modified S-curve membership function. A recursive improved tabu search has been used to solve this fuzzy optimization problem. Tremendously improved results are obtained for the optimal profit function and optimal solution for four crude oil. The accuracy of constraints satisfaction and the quality of the solutions are achieved successfully. © 2012 World Scientific Publishing Company.

Item Type: Article
Additional Information: cited By 35
Uncontrolled Keywords: Crude oil; Decision making; Linear programming; Oil fields; Optimization; Petroleum refineries; Profitability; Tabu search, Constraints satisfaction; Decision variables; Fuzzy linear programming problems; Improved Tabu search algorithm; Improved tabu searches; Large-scale problem; Level of satisfaction; Recursive techniques, Membership functions
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:51
Last Modified: 09 Nov 2023 15:51
URI: https://khub.utp.edu.my/scholars/id/eprint/3205

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