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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/109033

    Title: Optimization of Biodiesel Production Using Multi-Objective Genetic Algorithm
    Authors: Goharimanesh, Masoud;Lashkaripour, Ali;Akbari, Aliakbar
    Keywords: Fuel, Biodiesel;Triglycerides;Methyl Ester;Optimization;Genetic Algorithm
    Date: 2016-06
    Issue Date: 2016-12-27 09:19:40 (UTC+8)
    Publisher: 淡江大學出版中心
    Abstract: In this modern technological age, one of the challenges facing the transportation industry, is finding a less polluting substitute for diesel. Meanwhile, any kind of fuel due to the cetane number specified in a diesel cycle cannot be utilized. One of the alternatives for this is biodiesel which is indirectly obtained from animal fat in the presence of alcohol. Cost of biodiesel is more than that of conventional fuels; therefore, optimization of industrial production of biodiesel is with major importance. There are several methods to obtain the optimum temperature for biodiesel production process. In this paper, genetic algorithm, as one of the strongest evolutionary algorithms, has been applied to biodiesel production to obtain the best reaction parameters. Moreover, in order to have a robust optimization, multi objective genetic algorithm is employed. The achieved temperature point for maximizing biodiesel production was a wide range of temperature which can be illustrated as Pareto front to help making the final decision. This study was aimed to maximize the amount of Ester and Alcohol in this production and minimize the other products. This result can define a new strategy for industrial biodiesel production planning.
    Relation: Journal of Applied Science and Engineering 19(2), pp.117-124
    DOI: 10.6180/jase.2016.19.2.02
    Appears in Collections:[Journal of Applied Science and Engineering] v.19 n.1

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