• International Journal of Naval Architecture and Ocean Engineering
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• 제8권6호
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• 전자공학회논문지SC
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• 제38권4호
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• pp.1-10
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• 2001

본 논문에서는 이산 시간 어핀 Type III 퍼지 시스템의 안정도를 판정하고 이에 의하여 제어기를 설계하는 방식을 제안하도록 한다. 제안되는 안정도 해석 및 설계 방식은 컨벡스 최적화 기업에 근거한 방식으로， 우선 이산 시간 어핀 Type III 퍼지 시스템이 2차적으로 안정하게 되는 조건을 유도하도록 한다. 그 이후 이를 선형 행렬 부등식의 형태로 변형하여 수치적 접근방식을 제안하고 제안한 안정조건을 이용하여 어핀 Type III 퍼지 시스템으로 표현된 플랜트에 대하여 안정도가 보장되는 퍼지 제어기를 설계하도록 한다. 끝으로 컴퓨터 모의 실험을 통하여 제안한 방법의 타당성을 확인한다.

• 한국시뮬레이션학회논문지
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• 제26권1호
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• pp.39-46
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• 2017

은밀하게 침투하여 아군의 핵심자산으로 접근하는 표적 잠수함을 상시 감시하기 위하여 수중 해저면 위치에 최적의 고정형 수동탐지소나를 배치하는 것을 고려 할 수 있다. 수동탐지소나 배치 최적화를 위한 효과도 지수는 넓은 탐지영역과 위치추정가능성의 함수로 적용할 수 있는데 계절적인 요인, 해상상태, 표적 잠수함의 침투심도 등의 다양한 확률적 변이를 포함하고 있어서 효과도지수가 배치의 입력에 대하여 확률적으로 나타나는 특성을 갖는다. 본 논문에서는 다양한 파라메타의 입력조건에 대하여 확률적인 출력을 갖는 수동탐지소나의 배치에 대한 최적화 문제를 정의하였으며, DPSO(Discrete binary version of PSO) 방법을 사용하여 최적 배치 안을 도출하기 위한 모의기반의 절차를 제시하고 고찰하였다.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.234-240
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• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• Transactions on Control, Automation and Systems Engineering
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• 제2권3호
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• pp.163-168
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• 2000

The problems of mixed $H_2/H_{\infty}$ filtering design fer continuous and discrete time linear systems with time delay are investigated. The main purpose is to design a stable mixed $H_2/H_{\infty}$ filter which minimizes the H$_2$Performance measure satisfying a prescribed H$_{\infty}$ norm bound on the closed loop system in continuous-time case and discrete-time case, respectively. The sufficient conditions of existence of filter, the mixed $H_2/H_{\infty}$ filter design method, and the upper bound of performance measure are proposed by LMI(linear matrix inequality) techniques in terms of all finding variables. Also, we present optimization problems in order to get the optimal mixed $H_2/H_{\infty}$ filter in continuous and discrete time case, respectively.

• Architectural research
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• 제4권1호
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• pp.33-38
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• 2002

The objective of this study is the development of discrete optimum design algorithms which is based on the genetic algorithms. The developed algorithms was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses structures and the constraints are stresses and displacements. This study solves the problem by introducing the genetic algorithms. The genetic algorithms consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed discrete optimum design algorithms was verified by applying the algorithms to optimum design examples.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1999년도 제30회 추계학술대회
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• pp.167-173
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• 1999

This paper suggests a method to design the deep groove ball bearing for high-load capacity by using a genetic algorithm. The design problem of ball bearings is a typical discrete/continuous optimization problem because the deep groove ball bearing has discrete variables, such as ball size and number of balls. Thus, a genetic algorithm is employed to find the optimum values from a set of discrete design variables. The ranking process is proposed to effectively deal with the constraints in genetic algorithm. Results obtained fer several 63 series deep groove ball bearings demonstrated the effectiveness of the proposed design methodology by showing that the average basic dynamic capacities of optimally designed bearings increase about 9~34% compared with the standard ones.

• International Journal of Aeronautical and Space Sciences
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• 제10권1호
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• pp.112-121
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• 2009

This paper deals with supersonic air-breathing missile system. A supersonic air-breathing missile system has very complicated and incoherent thrust characteristics with respect to outer and inner environment during operation. For this reason, the missile system has many maneuver constraints and is allowed to operate within narrow flight envelope. In this paper, trajectory optimization of the missile is accomplished. The trajectory optimization problem is formulated as a discrete parameter optimization problem. For this formulation, Legendre Pseudo-Spectral method is introduced. This method is based on calculating the state and control variables on Legendre-Gauss-Lobatto (LGL) points. This approach helps to find approximated derivative and integration quantities simply. It is shown that, for this trajectory optimization, trend analysis is performed from thrust characteristics on various conditions so that the trajectory optimization is accomplished with fine initial guess with these results.

• Steel and Composite Structures
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• 제24권1호
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• pp.129-140
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• 2017

Structural optimization is one of the popular and active research areas in the field of structural engineering. In the present study, the newly developed moth-flame optimization (MFO) algorithm and its enhanced version termed as enhanced moth-flame optimization (EMFO) are employed to implement the optimization process of planar and 3D steel frame structures with discrete design variables. The main inspiration of this optimizer is the navigation method of moths in nature called transverse orientation. A number of benchmark steel frame optimization problems are solved by the MFO and EMFO algorithms and the results are compared with those of other meta-heuristics. The obtained numerical results indicate that the proposed EMFO algorithm possesses better computational performance compared with other existing meta-heuristics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.592-595
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• 1999

In this paper, we propose a unified method to solve the various robust filtering problem for a class of uncertain discrete time systems. Generally, to solve the robust filtering problem, we must convert the convex optimization problem with uncertainty blocks to the uncertainty free convex optimization problem. To do this, we derive the robust matrix inequality problem. This technique involves using constant scaling parameter which can be optimized by solving a linear matrix inequality problem. Therefore, the robust matrix inequality problem does not conservative. The robust filter can be designed by using this robust matrix inequality problem and by considering its solvability conditions.