• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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• pp.248-250
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• 2008

본 논문은 GP(Genetic Programming)을 이용한 4족 보행 로봇의 새로운 걸음새 생성 방식에 대해 소개한다. 4족 보행로봇의 걸음새 생성문제는 다양한 파라미터를 통시에 최적화해야 하는 매우 어려운 문제이다. 본 논문에서는 GP를 기반으로 관절좌표계에서 로봇의 관절 궤석을 직접 제어하는 방식을 사용한다. 이는 기존의 특정한 형태의 발끝의 자취를 사용하는 방법들에 비해 효율적이며 구조적으로 제한피지 않는 특징을 가진다. 또한, 새로운 트리구조기반의 GP 연산자의 적용을 통해 더 좋은 결과를 얻을수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1871-1875
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• 1997

Crane operation is manually accomplished by skilled operators. Recently, the concept of automation is widely introduced in shipping and unloading operation using the overhead crane for the enhanced productivity. In this regards, we designed an angle detector and 3D position detectro which are key evices for this operation. As well as an intellignet control algorithm is developed for the implementation of swing free crane. The performance of the presented algorithm is tested for the swing angle and the position of the overheas crand. The control scheme adopts a feedback control of an angular velocity of swing in initial phase and then the fuzzy controller whose rule base is optimized by a genetic algorithm.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.166-169
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• 1997

For parallel processing, the compiler partitions a loaded program into a set of tasks and makes a schedule for the tasks that will minimize parallel processing time for the loaded program. Building an optimal schedule for a given set of partitioned tasks of a program has known to be NP-complete. In this paper we introduce a GA(Genetic Algorithm)-based scheduling method in which a chromosome consists of two parts of a string which decide the number and order of tasks on each processor. An additional computation is used for feasibility constraint in the chromosome. By granularity theory, a partitioned program is categorized into coarse-grain or fine-grain types. There exist good heuristic algorithms for coarse-grain type partitioning. We suggested another GA adaptive to the coarse-grain type partitioning. The infeasibility of chromosome is overcome by the encoding and operators. The number of processors are decided while the GA find the minimum parallel processing time.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.225-228
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• 2001

DNA computing has been applied to the problem of getting an optimal solution since Adleman's experiment. DNA computing uses strings with various length and four-type bases that makes more useful for finding a global optimal solutions of the complex multi-modal problems. This paper presents DNA coding method for finding optimal solution of the multi-modal function and compares the efficiency of this method with the genetic algorithms (GA). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string and DNA coding method uses a tool of calculation or Information store with DNA molecules and four-type bases denoted by the symbols of A(Ademine), C(Cytosine), G(Guanine) and T(Thymine). The same operators, selection, crossover, mutation, are applied to the both DNA coding algorithm and genetic algorithms. The results show that the DNA based algorithm performs better than GA.

• 한국경영과학회지
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• 제23권4호
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• pp.187-201
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• 1998

In ATM networks with high capacity, the effect of failures on transmission links or nodes can be catastrophic, so that the issue of survivability is of great importance. In this paper. we consider the routing problem for working and backup virtual paths(VPs). To accomplish a higher survivability. routing the two kinds of VPs should be taken into account at the same time because backup VP routing depends on the working VP routing. A coevolutionary algorithm is employed to solve the problem for simultaneously routing of working and backup VPs. To develop an efficient coevolutionary algorithm for the problem. structure of populations, encoding method, neighborhood, and genetic operators are studied in this paper. The results of extensive experiments are reported. The performance comparison of the proposed algorithm with a conventional genetic algorithm and existing heuristics shows that our approach is promising.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.137-141
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• 2000

This paper presents an application of a new Adaptive Genetic Algorithms(AGA) to solve the Optimal Routing problem(ORP) for distribution system planning. In general, since the ORP is modeled as a mixed integer problem with some various mathematical constraints, it is hard to solve the problem. In this paper, we proposed a new adaptive strategy in GA to overcome the premature convergence and improve the convergence efficiency. And for these purposes, we proposed a fitness function suited for the ORP. In the proposed AGA, we used specially designed adaptive probabilities for genetic operators to consider the characteristics of distribution systems that are operated under radial configuration. The proposed algorithm has been tested in sample networks and the results are presented.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2003년도 International Meeting on Information Display
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• pp.730-733
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• 2003

Dual coding technique is one of the popular techniques to reduce the dynamic false contours on PDP. Subfield pattern is a key factor affecting the performance of dual coding technique. In this paper, an optimum subfield selection method based on genetic algorithm is proposed. Two types of string structures are defined to account for all the possible configurations of the dual coding subfield patterns. Genetic operators are proposed for optimization of dual coding subfield pattern. Quantitative measures to describe degrees of dynamic false contours and checkerboard patterns are defined. Experimental results indicate that dual coding subfield pattern that is determined by proposed method reduces dynamic false contours and checkerboard patterns.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1995년도 추계학술발표회논문집(1)
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• pp.123-128
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• 1995

A classical PID controller is designed by applying the GA (Genetic Algorithm) which searches the optimal parameters through three major operators of reproduction, crossover and mutation under the given constraints. The GA could minimize the designer's interference and the whole design process could easily be automated. In contrast with other traditional PID design methods which allows for the system output responses only, the design with the GA can take account of the magnitude or the rate of change of control input together with the output responses, which reflects the more realistic situations. Compared with other PIDs designed by the traditional methods such as Ziegler and analytic, the PID by the GA shows the superior response characteristics to those of others with the least control input energy.

• 한국지능시스템학회논문지
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• 제10권4호
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• pp.379-389
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• 2000

A cellular automaton is well-known for self-organizing and dynamic behavions in the filed of artifial life. This paper addresses a new neuronic architecture called an evolvable celluar classifier which evolves with the genetic rules (chromosomes) in the non-uniform cellular automata. An evolvable cellular classifier is primarily based on cellular programming, but its mechanism is simpler becaise it utilizes only mutations for the main genetic operators and resmbles the Hopfield network. Therefore, the desirable bit-patterns could be obtained through evolutionary processes for just one individual agent, As a rusult, an evolvable hardware is derived which is applicable to clessification of bit-string information.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 춘계학술대회
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• pp.523-534
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• 2005

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.