• 한국공간구조학회논문집
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• 제2권3호
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 한국자동차공학회논문집
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• 제7권8호
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• pp.208-215
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• 1999

Using the orthogonal arrays and the occupant analysis software based on the multi-body dynamics , two interactive design algorithms are proposed to improve the initial design of the occupant protection systems. Algorithm 1 sequentially moves the narrow design space within the upper and the lower design limit. Algorithm 2 sequentially reduces the relatively wide design space. Each design algorithm is composed of two levels . The first level is to improve the characteristics of the crash performance considering the noise factors. In order to obtain the robust design, the second level reduces the variations the noise factors. In order to obtain the robust design, the second level reduces the variations due to the tolerance of the design variable. To utilize the algorithm 1, HIC(Head Injury Criterion) , 3 msec criterion value of the chest acceleration and the femur load decreased by 27.4%, 10.4% and 55.8%, respectively. To utilizer the algorithm 2 , the results decreased by 38.0%, 10.5% and 3.0% , respectively.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제3B권3호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.655-658
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• 1997

In this paper, we intend to develop optimized design algorithm by deciding design parameters which are considered in the first design stage of inkjet printer head. thus, the parameters are such as electric pulse, input voltage of actuator to operate actuator, shape dimension of actuator an so on. in the first design stage, according to such parameters, a lot of time and money to develop inkject printer head are needed. to reduce trial and error and to save development time in the first design stage, optimized design algorithm is required all the more. design algorithm was developed via commercial FE analysis code(ANSYS & COENTOR) for the readability and convenience of algorithm. the reasonability of algorithm was verified by implementing analysis of system stage based on the data of piezoelectric actuator which was designed through algorithm.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.858-863
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• 2004

In the optimized design of an actual structure, the design variable should be selected among any certain values or corresponds to a discrete design variable that needs to handle the size of a pre-formatted part. Various algorithms have been developed for discrete design. As recently reported, the sequential algorithm with orthogonal arrays(SOA), which is a local minimum search algorithm in discrete space, has excellent local minimum search ability. It reduces the number of function evaluation using orthogonal arrays. However it only finds a local minimum and the final solution depends on the initial value. In this research, the genetic algorithm, which defines an initial population with the potential solution in a global space, is adopted in SOA. The new algorithm, sequential algorithm with orthogonal arrays and genetic algorithm(SOAGA), can find a global solution with the properties of genetic algorithm and the solution is found rapidly with the characteristics of SOA.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2004년도 춘계 학술발표회 논문집 제1권1호(통권1호)
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 한국공간구조학회논문집
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• 제3권4호
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• pp.59-67
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• 2003

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. Genetic algorithm tends to thrive in an environment in which the search space is uneven and has many hills and valleys. In this study, genetic algorithm is used for solving the design problem of gable structure. The design problem of frame structure has some special features(complicate design space, many nonlinear constrants, integer design variables, termination conditions, special information for frame members, etc.), and these features must be considered in the formulation of optimization problem and the application of genetic algorithm. So, 'FRAME operator', a new genetic operator for solving the frame optimization problem effectively, is developed and applied to the design problem of gable structure. This example shows that the new opreator has the possibility to be an effective frame design operator and genetic algorithm is suitable for the frame optimization problem.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.415-422
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• 1999

This paper describes a new optimum design approach for piled raft foundations using the genetic algorithm. The objective function considered is the cost-based total weight of raft and piles. The genetic algorithm is a search or optimization technique based on nature selection. Successive generation evolves more fit individuals on the basis of the Darwinism survival of the fittest. In formulating the genetic algorithm-based optimum design procedure, the analysis of piled raft foundations is peformed based on the 'hybrid'approach developed by Clancy(1993), and also the simple genetic algorithm proposed by the Goldberg(1989) is used. To evaluate a validity of the optimum design procedure proposed based on the genetic algorithm, comparisons regarding optimal pile placement for minimizing differential settlements by Kim et at.(1999) are made. In addition using proposed design procedure, design examples are presented.

• 제어로봇시스템학회논문지
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• 제10권11호
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• pp.1071-1076
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• 2004

It is a fuzzy controller that it is the most used method in the control of non-linear system. The most important part in the fuzzy controller is a design of fuzzy rules. Many algorithm that design fuzzy rules have proposed. And attention to the evolutionary computation is increasing in the recent days. Among them, the co-evolutionary algorithm is used in the design of optimal fuzzy rule. This paper takes advantage of a schema co-evolutionary algorithm. In order to verify the efficiency of the schema co-evolutionary algorithm, a fuzzy controller for the mobile robot control is designed by the schema co-evolutionary algorithm and it is compared with other parasitic co-evolutionary algorithm such as a virus-evolutionary genetic algorithm and a co-evolutionary method of Handa.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.400-403
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• 2004

This paper presents an optimum design of journal bearings using a hybrid method to find the solutions of optimization problem. The present hybrid algorithm, namely Enhanced Artificial Life Algorithm(EALA), is a synthesis of an artificial life algorithm(ALA) and the random tabu search(R-tabu) method. EALA is applied to the optimum design of journal bearings supporting simple rotor. The applicability of EALA to optimum design of rotor-bearing system is exemplified through this study.