• Title/Summary/Keyword: Multi Objective Genetic Algorithm

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Optimization of Turbofan Engine Design Point by using Seven Level Orthogonal Array (7수준 직교배열을 적용한 터보팬 엔진 설계점 최적화)

  • Kim, Myungho;Kim, Youil;Lee, Kwangki;Hwang, Kiyoung;Min, Seongki
    • Journal of the Korean Society of Propulsion Engineers
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    • v.17 no.4
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    • pp.10-15
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    • 2013
  • For design optimization, engineers should require the accurate information of design space and then explore the design space and carry out optimization. Recently, the total design framework, based on design of experiments and optimization, is widely used in industry areas to explore the design space above all. For optimizing turbofan engine design point, the response surface model is constructed by using the 7 level orthogonal array which satisfies the statistical uniformity and orthogonality and gets the dense design space information. The multi-objective genetic algorithm is used to find the optimal solution within the given constraints for finding global optimal one in response surface model. The optimal solution from response surface model is verified with GasTurb simulation result.

Development of Bridge Maintenance Method based on Life-Cycle Performance and Cost (생애주기 성능 및 비용에 기초한 교량 유지관리기법 개발)

  • Park, Kyung Hoon;Kong, Jung Sik;Hwang, Yoon Koog;Cho, Hyo Nam
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6A
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    • pp.1023-1032
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    • 2006
  • In this paper, a new method for the bridge maintenance is proposed to overcome the limit of the existing methods and to implement the preventive bridge maintenance system. The proposed method can establish the lifetime optimum maintenance strategy of the deteriorating bridges considering the life-cycle performance as well as the life-cycle cost. The lifetime performance of the deteriorating bridges is evaluated by the safety index based on the structural reliability and the condition index detailing the condition state. The life-cycle cost is estimated by considering not only the direct maintenance cost but also the user and failure cost. The genetic algorithm is applied to generate a set of maintenance scenarios which is the multi-objective combinatorial optimization problem related to the life-cycle cost and performance. The study examined the proposed method by establishing a maintenance strategy for the existing bridge and its advantages. The result shows that the proposed method can be effectively applied to deciding the bridge maintenance strategy.