• 품질경영학회지
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• 제41권3호
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• pp.371-380
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• 2013

Purpose: This study analyzes the optimal operation scheme of childcare centers in Korea to maximize the quality of childcare service by determining the number of children and number of teachers. Methods: This study employs a mathematical programming methodology called 'nonlinear integer programming (NLIP)' to solve the optimization problems and compare the quality of childcare service of optimal solutions with those of present operation scheme. Results: It is very successful in obtaining the optimal solutions for alternative capacities and they guarantee the substantial improvement in the quality of childcare service. Conclusion: Though more variables should be adapted for defining the quality of childcare service robustly, it is possible to conclude that childcare centers should modify their operation scheme to improve the quality of childcare service.

• 조명전기설비학회논문지
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• 제24권8호
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• pp.8-14
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• 2010

본 논문에서는, 제주지역 전력계통에 설치되는 배터리 저장장치의 최적용량을 산정하였다. 본 논문에서 검토한 내용은, 제주지역의 '06~'07년도 실제 전력사용데이터를 바탕으로 '06~'16년도까지의 전력사용량을 추정한 후, 4차 전력수급계획에 따른 전력설비 증감계획데이터를 사용, 최대전력저감, 전력량 요금저감, 정전발생비용저감, 3가지 측면에서 배터리 저장장치의 용량별 얻을 수 있는 이득을 계산하고, 최적용량을 제시하였다.

• 전기학회논문지
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• 제59권7호
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• pp.1232-1236
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• 2010

In this Paper, optimal capacity of energy storage and amount of $CO_2$ reduction in Jeju is calculated. Based on electricity demand data of Je-Ju from 2006 to 2007, the estimation electricity demand from 2009 to 2018 is performed. To calculate the amount of maximum $CO_2$ reduction and energy storage capacity in Jeju, the 4th power supply planning and IPCC guideline are used. Finally, Optimal capacity of energy storage and the amount of $CO_2$ reduction are showed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3060-3062
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits (CNC) is proposed. The proposed algorithm compute the optimal path using subgoal-based dynamic programming algorithm. In the algorithm, the optimal paths are computed regardless of the distance between the initial and the goal position. It begins to find subgoals starting from the initial position when the output of the initial cell becomes nonzero value. The suboal is set as the initial position to find the next subgoal until the final goal is reached. Simulations have been done considering the imprecise hardware fabrication and the limitation of the magnitude of input value.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.360-362
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• 2003

In operation of distribution system, DGs(Distributed Generations) are installed as an alternative of extension and establishment of substations, transmission and distribution lines according to increasing power demand. Optimal capacity and allocation of DGs improve power quality and reliability. This paper proposes a method for determining the optimal number, size and allocation of DGs needed to minimize operation cost of distribution system. Capacity of DGs for economic operation of distribution system can be estimated by the load growth and line capacity during operation planning duration. DG allocations are determined to minimize total cost with failure rate and annual reliability cost of each load point using GA(Genetic Algorithm).

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.354-360
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• 1998

In general, it is very difficult to find optimal fuzzy rules by experience when a system is dynamical and/or complex. Futhermore proper fuzzy partitioning is not deterministic and there is no unique solution. Therefore we propose a new design method of an optimal fuzzy logic controller, that is a co-evolutionary genetic algorithm finding optimal fuzzy rule and proper membership functions at the same time. We formalize the relation between fuzzy rules and membership functions in terms of fitness. We review the typical approaching methods to co-evolutionary genetic algorithms , and then classify them by fitness relation matrix. Applications of the proposed method to a path planning problem of autonomous mobile robots when moving objects exist are presented to demonstrate the performance and effectiveness of the method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.151-153
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• 2003

This paper proposes determining a optimal number, size and allocation of DGs(Distributed Generations) needed to minimize operation cost of distribution system, obtains economic benefit in operation planning of DG and improves system reliability. System reliability is assessed whether DG install and reliability cost consider. DG optimal allocations are determined to minimize total cost with power buying cost, operation cost of DG, loss cost and outage cost using GA(Genetic Algorithm). And it was determined installed load-point and order.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.395-398
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• 1993

This paper proposes an algorithm to find an optimal trajectory for unspecified paths of the tips of two arms of a dual arm robot. The effective handling a specified object of a dual arm robot closely depends on the effective collision avoidance between parts of robot and the object. For time optimal trajectory without collision, a graphical method is applied for a robot with two degree of freedom. The effectiveness of the proposed method is demonstrated by some simulation results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1216-1218
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• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• Journal of Electrical Engineering and Technology
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• 제5권1호
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• pp.45-53
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• 2010

This paper presents an improved parallel particle swarm optimization approach (IPPSO) based decomposed network for economic power dispatch with discontinuous fuel cost functions. The range of partial power demand corresponding to the partial output powers near the global optimal solution is determined by a flexible decomposed network strategy and then the final optimal solution is obtained by parallel Particle Swarm Optimization. The proposed approach tested on 6 generating units with smooth cost function, and to 26-bus (6 generating units) with consideration of prohibited zone effect, the simulation results compared with recent global optimization methods (Bee-OPF, GA, MTS, SA, PSO). From the different case studies, it is observed that the proposed approach provides qualitative solution with less computational time compared to various methods available in the literature survey.