• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.64-66
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• 1995

This paper presents a new approach to evaluate optimal basic reliability indices of electric distribution systems using genetic algorithm. The use of optimal reliability evaluation is an important aspect of distribution system planning and operation to determine adequacy reliability level of each area. In this paper, the reliability model is based on the analytical method, connecting component failure to load point outage in each section. The proposed method applies genetic algorithm to calculate the optimal values of basic reliability indices, ie. failure rate and repair time, for a load point in the power distribution system, subject to minimizing interruption cost. Test results for the model system are reported in the paper compared with a direct optimization method(gradient projection).

• EDISON SW 활용 경진대회 논문집
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• 제4회(2015년)
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• pp.479-483
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• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• 설비공학논문집
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• 제17권2호
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• pp.140-146
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• 2005

The on-line optimal control algorithm for central heating system has been researched for minimizing energy consumption while maintaining the comfort of indoor thermal environment in terms of the environmental variables such as indoor heating load and outdoor temperature variation. This study has been done by using TRNSYS Program in order to analyze the central heating system. The optimal control algorithm shows good energy Performances in comparison with the conventional one.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 춘계학술대회 학술발표 논문집
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• pp.116-119
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• 1998

Abstract-In paper, an operation support software for combustion control of refuse incineration plant is developed using fuzzy model and genetic algorithm. It has two major modules which are simulation module and optimal operation module. In simulation module modelling is performed to obtain fuzzy model of the refuse incineration plant and obtained fuzzy model predicts outputs of the plant when inputs are given. This module can be used to obtain control strategy, and train and enhance operators' skill by simulating the plant. And in optimal operation module, genetic algorithm searches and finds out optimal control inputs over all possible solutions in respect to desired outputs. In order to testify proposed operation support software, computer simulation was carried out.

• Smart Structures and Systems
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• 제20권5호
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• pp.607-618
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• 2017

In this research, a newly developed nature-inspired optimization method, the Lion Pride Optimization algorithm (LPOA), is utilized for optimal design of composite steel box girder bridges. A composite box girder bridge is one of the common types of bridges used for medium spans due to their economic, aesthetic, and structural benefits. The aim of the present optimization procedure is to provide a feasible set of design variables in order to minimize the weight of the steel trapezoidal box girders. The solution space is delimited by different types of design constraints specified by the American Association of State Highway and Transportation Officials. Additionally, the optimal solution obtained by LPOA is compared to the results of other well-established meta-heuristic algorithms, namely Gray Wolf Optimization (GWO), Ant Lion Optimizer (ALO) and the results of former researches. By this comparison the capability of the LPOA in optimal design of composite steel box girder bridges is demonstrated.

• 한국인터넷방송통신학회논문지
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• 제11권1호
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• pp.165-170
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• 2011

Pfair 알고리즘은 다중 프로세서 환경에서 경성 실시간 태스크 집합을 스케줄링 하는 최적 알고리즘인데, 고정된 퀀텀 크기를 기반으로 한다. 최근 mode change 환경에서 도달 함수를 이용하여 최적 퀀텀을 동적으로 결정하는 방법들이 제안되었는데, 이 방법들에서는 최적 퀀텀을 구하기 위해 순차 탐색을 해야 되는 경우가 많이 발생하였다. 본 논문에서는 개선된 도달 함수를 이용하여 최적 퀀텀을 보다 빠르게 구할 수 있는 새로운 방법을 제안하였다.

• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.207-212
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• 2008

This paper presents a robust and computationally efficient optimal design algorithm for electromagnetic devices by combining an adaptive response surface approximation of the objective function and($1+{\lambda}$) evolution strategy. In the adaptive response surface approximation, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design with the Max Distance and Min Distance criteria. The proposed algorithm is applied to an analytic example and TEAM problem 22, and its robustness and computational efficiency are investigated.

• 대한전기학회논문지:전력기술부문A
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• 제54권12호
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• pp.597-602
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• 2005

The introduction of competition in electricity market emphasizes the importance of sufficient transmission capacities to guarantee various electricity transactions. Therefore, when dispatch scheduling, transmission security constraints should be considered for the economic and stable electric power system operation. In this paper, we propose an optimal dispatch scheduling algorithm incorporating transmission security constraints. For solving these constraints, the dispatch scheduling problem is decomposed into a master problem to calculate a general optimal power flow (OPF) without transmission security constraints and several subproblems to inspect the feasibility of OPF solution under various transmission line contingencies. If a dispatch schedule given by the master problem violates transmission security constraints, then an additional constraint is imposed to the master problem. Through these iteration processes between the master problem and subproblems, an optimal dispatch schedule reflecting the post-contingency rescheduling is derived. Moreover, since interruptible loads can positively participate as generators in the competitive electricity market, we consider these interruptible loads active control variables. Numerical example demonstrates efficiency of the proposed algorithm.

• 한국정밀공학회지
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• 제19권8호
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• pp.147-154
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• 2002

In this paper, a path navigation algorithm through use of a sensor platform is proposed. The sensor platform is composed of two electric motors which make panning and tilting motions. An algorithm for computing a real path and an obstacle length is developed by using a scanning method that controls rotation of the sensors on the platform. An Autonomous Robot Vehicle(ARV) can perceive the given path by adapting this algorithm. A sensor scanning method is applied to the sensor platform for using small numbers of sensor. The path navigation algorithm is composed of two parts. One is to perceive a path pattern, the other is used to avoid an obstacle. An optimal controller is designed for tracking the reference path which is generated by perceiving the path pattern. The ARV is operated using the optimal controller and the path navigation algorithm. Based on the results of actual experiments, this algorithm for an ARV proved sufficient for path navigation by small number of sensors and for a low cost controller by using the sensor platform with a scanning method.

• 한국소음진동공학회논문집
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• 제12권12호
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• pp.935-942
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• 2002

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.