• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.3
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• pp.128-132
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• 2003

This paper presents the optimum design of a Linear Induction Motor (LIM) using Genetic algorithm, Niching Genetic algorithm and Neural Network. The design variables are optimized by different optimization methods and the results are discussed.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.214-216
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• 1999

This paper discussed an optimal designs of 2 pole fan motors in refrigerator using a Niching Algorithm. We applied a Niching method to multi-objective optimal design of air gap construct. This Niching genetic algorithm is called "Restricted Competition Selection"(RCS) that is suitable for real world problem such as shape or structural optimization of electromagnetic device. The finite element method being used for nonlinear numerical characteristic analysis is provided exact solution in the system. Through this process is reduced the cogging torque ripple in air gap.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.783-788
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• 2008

This paper presents the mechanism of the machine and the numerical result of attractive force in the Electro-Permanent Magnet Lifter (EPML) and an improved niching Genetic Algorithm (GA) applying the concept of auto-tuning and detecting traces. Population size and both (right and left) niche radii of each peak in an asymmetrical objective function can be determined automatically. The validity of the proposed method is verified by simulation results.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.5
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• pp.234-241
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• 2002

An optical pickup actuator is an objective-lens-moving mechanism that provides a means to follow the disk displacement accurately(1). In this paper, a slim type optical pickup actuator for Notebook PCs is analyzed and designed to improve the driving sensitivity A three dimensional equivalent magnetic circuit network method (3D-EMCN method) is proposed for an analysis method which provides better characteristics in both precision and computation time of analysis comparing with a commercial three-dimensional finite element (3D-FEM) codes. To verify the validity of proposed method, we made a comparison between the analysis results and the experimental ones. We also compared this analysis results with 3D-FEM results. Among the several optimal algorithm, we adopt a niching genetic algorithm, which renders a set of the multiple optimal solutions. RCS (Restricted Competition Selection) niching genetic algorithm is used for optimal design of the actuator's performance. Recently, the pickup actuator needs additional driving structure for radial and tangential tilting motion to obtain better pick-up performance. So we applied the proposed method to the model containing tilting coils.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.76-78
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• 1998

Niching methods extend genetic algorithms to domains that require the location of multiple solutions. But, current niching methods have some of drawbacks in the ability of search and preservation of solutions. So, this paper presents a new technique, named as Restricted Competition Selection(RCS). Then, RCS method is compared with sharing and deterministic crowding by applying to some multimodal problems in order to verify that it has more favorable properties.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.7
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• pp.323-330
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• 2001

Niching method enables the genetic algorithm(GA) to be applied to the problems that require the location of multiple solutions in the search space, but these methods have fatal disadvantages. The main disadvantage is that the method requires too much calculation of object function. In this paper, a niching method using restricted competition selection(RCS) combined with a pattern search method(PSM) is proposed to identify multiple niches more efficiently and fast in a multimodal domain. The validity of the proposed method is verified by the simulation of test functions and the optimal design of an torque motor.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.717-719
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• 2000

In this paper, we discussed an optimal design of BLDC motor using rare earth magnet. In motor design using rare earth magnet, because of the characteristics that rare earth magnets have high remanence, the effect of saturation of steel has to be considered. For this, we used nonlinear finite clement method. For optimal design, a Niching genetic algorithm is used. As a result, we found out a set of BLDC motor shapes increasing motor efficiency, and decreasing cogging torque.

• Journal of the Korean Magnetics Society
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• v.8 no.3
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• pp.169-177
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• 1998

In the case of an induction motor efficiency optimal design for electric vehicle which is a real world problem, several different designs are almost equal in terms of efficiency. But these designs may have the differences in terms of other characteristics such as power factor, temperature rise, material cost, and ease of manufacture. Therefore it is necessary that an optimization routine suggests various possible solution alternatives and a designer selects optimal solution among them using other characteristics, his experience and judgment. In this paper new niching genetic algorithm and the rating function method to select the optimal point among possible optimal solution alternatives are presented.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.388-390
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• 1999

This paper discusses an optimal design of high space factor BLDC motor. Because of high space factor BLDC, Nonliear finite element method considering saturation of outer-rotor is used. For optimal design, a new niching genetic algorithm, namely "Restricted Competitions Selection" is used. This algorithm constructs an objective function using only the most important criteria and provides a designer with a set of solution rather than one solution. To verify its effectiveness, the new niching genetic algorithm is applied to an actual high space factor BLDC motor We show that a new designed high space factor BLDC motor is superior to the actual high space factor BLDC.

• Steel and Composite Structures
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• v.15 no.5
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• pp.519-538
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• 2013

The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. Previous GAs in the literature were characterized by poor convergence, including slow progress, that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.