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

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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)

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.

Suggested Citation

  • Pandian M. Vasant & Timothy Ganesan & Irraivan Elamvazuthi, 2012. "Hybrid Tabu Search Hopfield Recurrent ANN Fuzzy Technique to the Production Planning Problems: A Case Study of Crude Oil in Refinery Industry," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), IGI Global, vol. 2(1), pages 47-65, January.
    • Handle: RePEc:igg:jmmme0:v:2:y:2012:i:1:p:47-65
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    Cited by:

    1. Ganesan, T. & Elamvazuthi, I. & Ku Shaari, Ku Zilati & Vasant, P., 2013. "Swarm intelligence and gravitational search algorithm for multi-objective optimization of synthesis gas production," Applied Energy, Elsevier, vol. 103(C), pages 368-374.

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