• Journal of Korean Society for Quality Management
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• v.41 no.3
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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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.8-14
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• 2010

In this Paper, optimal capacity of battery storage in Je-Ju is calculated. First, Electricity demand data of Je-Ju('06~'16) is estimated based on real electricity demand data of Je-Ju('06~'07). Then, the 4th power supply planning is used to calculate benefits from battery storage capacity in view of maximum power savings, preventing outages savings and energy charge fee reduction. Finally, optimal battery storage capacity is suggested.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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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.

• Proceedings of the KIEE Conference
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• 2000.07d
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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.

• Proceedings of the KIEE Conference
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• 2003.07a
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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).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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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.

• Proceedings of the KIEE Conference
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• 2003.11a
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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.

• Proceedings of the KIEE Conference
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• 1993.07a
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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.

• Proceedings of the KIEE Conference
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• 1996.07b
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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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• v.5 no.1
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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.