Hybrid Optimization Techniques for Optimization in a Fuzzy Environment
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. These techniques are performed under the consideration of some real assumptions. In current studies, we still have severa...
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| 主要な著者: | , , |
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| フォーマット: | 論文 |
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2013
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| オンライン･アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885453891&doi=10.1007%2f978-3-642-30504-7_40&partnerID=40&md5=82ca3ad4e58cdc549fa6d9e5e3535ee6 http://eprints.utp.edu.my/32742/ |
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| 要約: | 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. These techniques are performed under the consideration of some real assumptions. In current studies, we still have several problems that require the application of fuzzy linear, non-linear, non-continues and other mathematical programming techniques. The prime objective of this chapter is to investigate a new application to the literature and to solve the crude oil refinery production problem by using the hybrid optimization techniques such as; Tabu Search (TS), Hopfield Recurrent Artificial Neural Network (HRANN) and fuzzy approaches. In this work, the real-world problem of the refinery model (which has been developed in (Gunes, 2000)) was solved using various optimization techniques. Thorough comparative studies and results analysis was carried out as well. The final findings reveal that the hybrid optimization technique provides better, robust, efficient, flexible and stable solutions. © Springer-Verlag Berlin Heidelberg 2013. |
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