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

CATEGORY: SCHEDULING
International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), Volume 2, Issue 1
Hybrid Tabu Search Hopfield Recurrent ANN Fuzzy Technique to the Production Planning Problems: A Case Study of Crude Oil in Refinery Industry
Pandian Vasant (Petronas University of Technology, Malaysia), Timothy Ganesan (Petronas University of Technology, Malaysia) and Irraivan Elamvazuthi (Petronas University of Technology, Malaysia)
Abstract
Fuzzy technology demonstrates that everything is a matter of degree. Many industrial production problems currently are solved by operational research optimization techniques, based on real assumptions. Here, the authors present several applications of fuzzy linear, non-linear, non-continues and other mathematical programming applications.
The authors’ primary objective is to investigate a new application to the literature and to solve the crude oil refinery production problem using the hybrid optimization techniques of Tabu Search (TS), Hopfield Recurrent Artificial Neural Network (HRANN) and fuzzy approaches.
They develop a real world problem of refinery model and conduct comparative studies on various optimization techniques. The final results and findings reveal that, the hybrid optimization technique provides solutions that are more robust, efficient, flexible and stable.
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