• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.231-236
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• 2001

The goal of multiphase optimization of machine structure is to obtain 1) light weight, 2) statically and dynamically rigid structure. The entire optimization process is carried out in two phases. In the first phase, multiple optimization problem with two objective functions is treated using pareto genetic algorithm. Two objective functions are weight of the structure, and static compliance. In the second phase, maximum receptance is minimized using genetic algorithm. The method is applied to design of quill type machine structure with back column.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.3
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• pp.44-50
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• 2017

This paper proposes arrival scheduling and advisory generation algorithms which can be used in the terminal airspace with Point-Merge procedures. The proposed scheduling algorithm consists of two steps. In the first step, the algorithm computes aircraft schedules at the entrance of the Point-Merge sequencing legs based on First-Come First-Served(FCFS) strategy. Then, in the second step, optimal sequence and schedules of all aircraft at the runway are computed using Multi-Objective Dynamic Programming(MODP) method. Finally, the advisories that have to be provided to the air traffic controllers are generated. To demonstrate the proposed algorithms, the simulation was conducted based on Jeju International Airport environments.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.103-105
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• 1992

The new approach using fuzzy linear programming with fuzzy multi-criterion is proposed for the best generation mix of a power system. A chracteristic feature of the presented approach is that not only cost but also reliability for goal function can be taken into account by using fuzzy multi-criterion and so more realistic solution can be obtained. The effectiveness of the proposed approach is demonstrated by the best generation mix problem of KEPCO-system size model which contains nuclear, coal, LNG, oil and pump-generator hydro plant in multi-years.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.205-210
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• 2007

The integration method of binary and real encoding in genetic algorithm is proposed to deal with design variables of various types in gear drive design. The method is applied to optimum design of multi-stage gear drive. Integer and Discrete type design variables represent the number of teeth and module, and continuous type design variables represent face width, helix angle and addendum modification factor etc. The proposed genetic algorithm is applied for the gear ratio optimization and the volume optimization(minimization) of multi-stage geared motor which is used in field. In result, the proposed design optimization method shows an effectiveness in optimum design process and the new design has a better results compared with the existing design.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.894-899
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• 2000

Optimization of 26 design variables selected from suspension characteristics for Korean High Speed Train (KHST) is performed according to the minimization of 58 responses which represent running safety and ride comfort for KHST and analyzed by using the each response surface model from stochastic design experiments. Sensitivity of design variables is also analyzed through the response surface model which ineffective design prameters to the performance index are screened by using stepwise regression method. The response surface models are used for optimizing design variables through simplex algorism. Values of performance index simulated by optimized design parameters are totally lower than those by initial design parameters. It shows that this method is effective for optimizing multi-design variables to multi-object function.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.46.2-46.2
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• 2009

탑재소프트웨어는 위성의 자세, 전력, 열 제어를 담당하는 소프트웨어로서 위성의 탑재컴퓨터 상에서 실행된다. 탑재소프트웨어는 추력기, 배터리, 온도조절장치와 같은 위성의 하드웨어 장치를 자치적으로 관리한다. 지상에서 위성을 운영할 수 있도록 탑재소프트웨어는 지상으로부터 명령을 받아서 처리하고, 위성의 텔레메트리 데이터를 지상으로 전송한다. 위성의 탑재소프트웨어를 프로그래밍하기 위하여 C 언어와 ADA 언어가 주로 사용된다. 이 논문에서는 소프트웨어 디자인과 하위레벨 프로그래밍 관점에서 C 언어와 ADA 언어를 비교 분석한다. 프로그래밍언어는 소프트웨어 디자인과 불가분의 관계에 있다. 이 논문은 프로그래밍언어와 함께 다목적실용위성과 통신해양기상위성의 소프트웨어 디자인을 소개한다. 다목적실용위성의 탑재소프트웨어는 절차 지향언어인 C로 작성되었으며, 함수 호출을 기반으로 설계되었다. 통신해양기상위성의 경우, 객체지향언어인 ADA로 작성되었으며, HOOD(Hierarchical Object-Oriented Design) 기법에 따라 모델링되었다. 탑재소프트웨어 프로그래밍언어는 위성의 탑재 하드웨어와 직접적으로 상호작용하도록 요구된다. 이 논문은 C와 ADA 언어가 메모리주소 및 로우 스토리지를 다루는 방법을 보여준다.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.233-235
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• 2003

This paper describes a new methodology to get pareto-optimal generation planning for decision-making. To get optimal generation planning consider total quantity of contamination for the specified term, authors employ dynamic programming. And, in the course of dynamic programming, pareto optimal solution can be obtained. So, a most proper solution can be selected by derision-maker. The usefulness is verified by applying It to the test system.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.149-157
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• 2004

This paper presents a new method for hi-objective optimization. Ordinary weighted sum method is easy to implement, but it has two significant drawbacks: (1) the solution distribution by the weighted sum method is not uniform, and (2) the method cannot determine any solutions that reside in non-convex regions of a Pareto front. The proposed adaptive weighted sum method does not solve a multiobjective optimization in a predetermined way, but it focuses on the regions that need more refinement by imposing additional inequality constraints. It is demonstrated that the adaptive weighted sum method produces uniformly distributed solutions and finds solutions on non-convex regions. Two numerical examples and a simple structural problem are presented to verify the performance of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.433-441
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• 2011

The optimization of a centrifugal compressor was conducted. The ANN (Artificial Neural Network) was adopted as an optimization algorithm, and it was learned and trained with the DOE (Design of Experiment). In the DOE, it was predicted the main effect and the interaction effect of design variables to the objective function. The ANN was improved in the optimization process using the GA (Genetic Algorithm). When any output at each generation was reached a standard level, it was re-calculated by the CFD (Computational Fluid Dynamics) and it was applied to develop a new ANN. After 6th generation, the prediction difference between ANN and CFD was less than 1%. A pareto of the efficiency versus the pressure ratio was obtained through the 21th generation. Using this method, the computational time for the optimization was equivalent to the time consumed by the gradient method, and the optimized results of multi-objective function were obtained.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2639-2641
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• 2003

유전자 알고리즘은 다윈의 자연선택설과 유전자의 진화 개념을 이용한 적응 탐색 알고리즘으로 적용하고자 하는 문제의 매개 변수를 유전자와 비슷한 데이터 구조로 부호화하고, 유전 연산자를 이용하여 문제의 해답을 찾는 알고리즘이다. 최근 유전자 알고리즘은 이러한 복수개의 목적 함수를 최적화 하기 위한 다중 최적화 문제를 위한 최적화 기술로서의 관심이 크게 다루어지고 있으며 전송 문제, 생산 공정 문제 계획 등과 같은 다목적 함수를 다루는 많은 응용 부분에 대해 적용되고 있다. 본 논문에서는 기본적인 다중 목적 함수용 예와 Gen과 Kim이 제안한 네트워크 신뢰도를 고려한 연결 비용과 메시지 지연을 고려한 이중 구속 통신망 설계 문제를 가지고 가중치 합과 여러 가지 파레토 방법들을 비교하고 연구 검토 하고자 한다.