Hybrid Tabu Search Hopfield Recurrent ANN Fuzzy Technique to the Production Planning Problems: A Case Study of Crude Oil in Refinery Industry

Pandian M. Vasant, Timothy Ganesan and Irraivan Elamvazuthi
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Pandian M. Vasant: Petronas University of Technology, Malaysia
Timothy Ganesan: Petronas University of Technology, Malaysia
Irraivan Elamvazuthi: Petronas University of Technology, Malaysia

International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), 2012, vol. 2, issue 1, 47-65

Abstract: The fuzzy technology reveals that everything is a matter of degree. At the moment, many industrial production problems are solved by operational research optimization techniques, under the considerations of some real assumptions. In this paper, the authors have several applications of fuzzy linear, non-linear, non-continues and other mathematical programming applications. The prime objective of this paper is to investigate a new application to the literature and to solve the crude oil refinery production problem by using the hybrid optimization techniques of Tabu Search (TS), Hopfield Recurrent Artificial Neural Network (HRANN) and fuzzy approaches. In application, the real world problem of refinery model has been developed and thorough comparative studies have been carried on varies optimization techniques. The final results and findings reveal that, the hybrid optimization technique provides better, robust, efficient, flexible and stable solutions.

Date: 2012
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