• 제목/요약/키워드: Multiobjective Design Optimization

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Methods of pairwise comparisons and fuzzy global criterion for multiobjective optimization in structural engineering

  • Shih, C.J.;Yu, K.C.
    • Structural Engineering and Mechanics
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    • 제6권1호
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    • pp.17-30
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    • 1998
  • The method of pairwise comparison inherently contains information of ambiguity, fuzziness and conflict in design goals for a multiobjective structural design. This paper applies the principle of paired comparison so that the vaguely formulated problem can be modified and a set of numerically acceptable weight would reflect the relatively important degree of multiple objectives. This paper also presents a fuzzy global criterion method ($FGCM_{\lambda}$) included fuzzy constraints that coupled with the objective weighting rank obtained from the modified pairwise comparisons for fuzzy multiobjective optimization problems. Descriptions in sequence of this combined method and problem solving experiences are given in the current article. Multiobjective design examples of truss and mechanical spring structures illustrate this optimization process containing the revising judgement techniques.

공진화전략에 의한 다중목적 유전알고리즘 최적화기법에 관한 연구 (A Study on Multiobjective Genetic Optimization Using Co-Evolutionary Strategy)

  • 김도영;이종수
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2000년도 추계학술대회논문집A
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    • pp.699-704
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    • 2000
  • The present paper deals with a multiobjective optimization method based on the co-evolutionary genetic strategy. The co-evolutionary strategy carries out the multiobjective optimization in such way that it optimizes individual objective function as compared with each generation's value while there are more than two genetic evolutions at the same time. In this study, the designs that are out of the given constraint map compared with other objective function value are excepted by the penalty. The proposed multiobjective genetic algorithms are distinguished from other optimization methods because it seeks for the optimized value through the simultaneous search without the help of the single-objective values which have to be obtained in advance of the multiobjective designs. The proposed strategy easily applied to well-developed genetic algorithms since it doesn't need any further formulation for the multiobjective optimization. The paper describes the co-evolutionary strategy and compares design results on the simple structural optimization problem.

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Optimization Design of Log-periodic Dipole Antenna Arrays Via Multiobjective Genetic Algorithms

  • Wang, H.J.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1353-1355
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    • 2003
  • Genetic algorithms (GA) is a well known technique that is capable of handling multiobjective functions and discrete constraints in the process of numerical optimization. Together with the Pareto ranking scheme, more than one possible solution can be obtained despite the imposed constraints and multi-criteria design functions. In view of this unique capability, the design of the log-periodic dipole antenna array (LPDA) using this special feature is proposed in this paper. This method also provides gain, front-back level and S parameter design tradeoff for the LPDA design in broadband application at no extra computational cost.

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유전자 알고리즘을 이용한 축류 송풍기 설계최적화 (Design Optimization of Axial Flow Fan Using Genetic Algorithm)

  • 이상환;안철오
    • 한국유체기계학회 논문집
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    • 제7권2호
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    • pp.7-13
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    • 2004
  • In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution agree well to the designer's weighting values, we proposed new multiobjective function which was the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach is effective for the case that the quality of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.

유전자 알고리즘을 이용한 축류 송풍기 설계최적화 (Design Optimization of Axial Flow Fan Using Genetic Algorithm)

  • 유인태;안철오;이상환
    • 유체기계공업학회:학술대회논문집
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    • 유체기계공업학회 2003년도 유체기계 연구개발 발표회 논문집
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    • pp.397-403
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    • 2003
  • In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution well agree to the designer's weighting values, we proposed new multiobjective function which is the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach will be effective for the case that the qualify of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.

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브러시리스 직류전동기의 다목적 최적설계 (Multiobjective Design Optimization of Brushless DC Motor)

  • 전연도;약미진치;이주;오재응
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권5호
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    • pp.325-331
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    • 2004
  • The multiobjective optimization (MO) problem usually includes the conflicting objectives and the use of conventional optimization algorithms for MO problem does not so good approach to obtain an effective optimal solution. In this paper, genetic algorithm (GA) as an effective method is used to solve such MO problem of brushless DC motor (BLDCM). 3D equivalent magnetic circuit network (EMCN) method which enables us to reduce the computational burden is also used to consider the 3D structure of BLDCM. In order to effectively obtain a set of Pareto optimal solutions in MO problem, ranking method proposed by Fonseca is applied. The objective functions are decrease of cogging torque and increase of torque respectively. The airgap length, teeth width and magnetization angle of PM are selected for the design variables. The experimental results are also shown to confirm the validity of the optimization results.

다중목적함수 진화 알고리즘을 이용한 마이크로어레이 프로브 디자인 (Microarray Probe Design with Multiobjective Evolutionary Algorithm)

  • 이인희;신수용;조영민;양경애;장병탁
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제35권8호
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    • pp.501-511
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    • 2008
  • 프로브(probe) 디자인은 성공적인 DNA 마이크로어레이(DNA microarray) 실험을 위해서 필수적인 작업이다. 프로브가 만족시켜야 하는 조건은 마이크로어레이 실험의 목적이나 방법에 따라 다양하게 정의될 수 있는데, 대부분의 기존 연구에서는 각각의 조건에 대하여 각자 독립적으로 정해진 한계치(threshold) 값을 넘지 않는 프로브를 탐색하는 방법을 취하고 있다. 그러나, 본 연구에서는 프로브 디자인을 두가지 목적함수를 지닌 다중목적함수 최적화 문제(multiobjective optimization problem)로 정의하고, ${\epsilon}$-다중목적함수 진화 알고리즘(${\epsilon}$-multiobjective evolutionary algorithm)을 이용하여 해결하는 방법을 제시한다. 제시된 방법은 19종류의 고위험군 인유두종 바이러스(Human Papillomavirus) 유전자들에 대한 프로브 디자인과 52종류의 애기장대 칼모듈린 유전자군(Arabidopsis Calmodulin multigene family)에 대한 프로브 디자인에 각각 적용되었다. 제안한 방법론을 사용하여 기존의 공개 프로브 디자인 프로그램인 OligoArray 및 OligoWiz에 비해 목표유전사에 더 적합한 프로브를 찾을 수 있었다.

A Method of Genetic Algorithm Based Multiobjective Optimization via Cooperative Coevolution

  • Lee, Jong-Soo;Kim, Do-Young
    • Journal of Mechanical Science and Technology
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    • 제20권12호
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    • pp.2115-2123
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    • 2006
  • The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

지식기반 최적설계시스템에 의한 선박 초기설계 (Preliminary Design of a Ship by the Knowledge-Based Optimum Design System)

  • 이동곤;김수영
    • 대한조선학회논문집
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    • 제33권1호
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    • pp.161-172
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    • 1996
  • 최적화기법을 포함한 종래의 전산 프로그램들은 수치적 계산과정과 그 결과에만 중점을 두고 개발되어 왔으며, 설계모델의 개발과 최적화기법의 선택 및 결과의 판단 등은 설계 전문가에 의하여 수행되어 왔다. 반면에 전문가의 경험적지식을 처리하는 지식기반시스템은 기호처리에 중점을 두고 있기 때문에 수치적 계산을 효과적으로 할 수 없다. 본 논문에서는 수치적인 계산결과만을 제공하는 최적화기법의 한계와 기호처리에 중점을 두고 있는 지식기반시스템의 한계를 극복하여, 보다 현실적인 최적설계안을 도출할 수 있는 지식기반 다목적함수 최적설계 시스템을, 최적화기법과 LISP 언어로 개발한 지식기반시스템을 통합하여 구현하고, 이를 LNG선의 최적설계 모델에 적용하여 개발된 시스템의 유용성을 보였다.

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Multiobjective optimum design of laminated composite annular sector plates

  • Topal, Umut
    • Steel and Composite Structures
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    • 제14권2호
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    • pp.121-132
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    • 2013
  • This paper deals with multiobjective optimization of symmetrically laminated composite angle-ply annular sector plates subjected to axial uniform pressure load and thermal load. The design objective is the maximization of the weighted sum of the critical buckling load and fundamental frequency. The design variable is the fibre orientations in the layers. The performance index is formulated as the weighted sum of individual objectives in order to obtain the optimum solutions of the design problem. The first-order shear deformation theory is used for the mathematical formulation. Finally, the effects of different weighting factors, annularity, sector angle and boundary conditions on the optimal design are investigated and the results are compared.