• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.39-42
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• 2000

진화 프로그래밍은 유전자 알고리즘과 함께 진화 연산 분야에 속하며 넓은 탐색공간에 존재하는 해를 찾는데 유용한 방법으로 알려져 있다. 본 논문에서는 이 두 가지 방법을 비교하기 위해서 Manabe 표준형을 기준으로 사용자의 요구사항에 맞는 스텝응답을 만족하는 계수, 즉 안정지수를 이 두 가지 방법을 적용하였다.

• 한국지능시스템학회논문지
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• 제16권2호
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• pp.228-233
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• 2006

This paper introduces design method for air pump system using bond graph and genetic programming to maximize outflow subject to a constraint specifying maximum power consumption. The air pump system is a mixed domain system which includes electromagnetic, mechanical and pneumatic elements. Therefore an appropriate approach for a better system for synthesis is required. Bond graphs are domain independent, allow free composition, and are efficient for classification and analysis of models. Genetic programming is well recognized as a powerful tool for open-ended search. The combination of these two powerful methods, BG/GP, was tested for redesign of air pump system.

• 한국환경생물학회:학술대회논문집
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• 한국환경생물학회 2001년도 학술대회
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• pp.133-133
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• 2001

• Computers and Concrete
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• 제19권6호
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• pp.651-658
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• 2017

High-performance concrete, besides aggregate, cement, and water, incorporates supplementary cementitious materials, such as fly ash and blast furnace slag, and chemical admixture, such as superplasticizer. Hence, it is a highly complex material and modeling its behavior represents a difficult task. This paper presents an evolutionary system for the prediction of high performance concrete strength. The proposed framework blends a recently developed version of genetic programming with a local search method. The resulting system enables us to build a model that produces an accurate estimation of the considered parameter. Experimental results show the suitability of the proposed system for the prediction of concrete strength. The proposed method produces a lower error with respect to the state-of-the art technique. The paper provides two contributions: from the point of view of the high performance concrete strength prediction, a system able to outperform existing state-of-the-art techniques is defined; from the machine learning perspective, this case study shows that including a local searcher in the geometric semantic genetic programming system can speed up the convergence of the search process.

• 한국지능시스템학회논문지
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• 제8권3호
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• pp.1-8
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• 1998

본 논문에서는 유전자 프로그래밍의 성능을 향상시키기 위하여 강화학습법에 기반한 강화 유전자 프로그래밍을 제안한다. 트리구조와 프로그램을 염색체로 가지는 유전자 프로그래밍(GP)은 다른 진화 알고리즘에 비해 염색체의 크기에 제한이 없기 때문에 표현력에 융통성이 많다는 장점이 있다. 그러나 이러한 특징은 반대고 교차 및 돌연변이 연산에 있어서 수렴성을 떨어뜨리는 단점을 나타낸다. 따라서 유전자 프로그래밍은 다른 진화알고리즘에 비해 개체군의 크기 및 진화 세대수를 크게 잡는 것이 일반적이다. 본 논문에서는 유전자 프로그래밍의 이러한 성질을 개선하기 위해서 프로그램에 강화신호를 주어 이것의 보답/벌칙의 정도에 기반한 교차 및 돌연번이 연산을 실행하는 방법을 제안한다. 제안된 방법은 인공개미(Artificial Ant)문제에 적용하여 그 유효성을 입증한다.

• 전기학회논문지
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• 제63권3호
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• pp.389-394
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• 2014

Two evolutionary gait generation methods for Cartesian and Joint coordinates space are compared to develop a fast locomotion for quadruped robots. GA(Genetic Algorithm) based approaches seek to optimize a pre-selected set of parameters for the locus of paw and initial position in cartesian coordinates space. GP(Genetic Programming) based technique generate few joint trajectories using symbolic regression in joint coordinates space as a form of polynomials. Optimization for two proposed methods are executed using Webots simulation for the quadruped robot which is built by Bioloid. Furthermore, simulation results for two proposed methods are analysed in terms of different coordinate spaces.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.624-629
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• 1998

Evolutionary computation techniques can solve search problems using simulated evolution based on the ‘survival of the fittest’. Recently, the genetic programming (GP) which evolves computer programs using the genetic algorithm was introduced. In this paper, the genetic programming technique is used in order to design a rule based controller consisting of condition-action rules for an unknown system. No a priori knowledge about the structure of the controller is needed. Representation of a solution, functions and terminals in GP are analyzed, and a method of constructing a fuzzy logic controller using the obtained rule based controller is described. A simulation example using a nonlinear system shows the validity and efficiency of the proposed method.

• 전기학회논문지
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• 제65권12호
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• pp.2069-2074
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• 2016

This paper presents a methodology based on evolutionary optimization for simultaneously optimizing design parameters of controller and components of plant. Genetic programming(GP) based bond graph model generation is adopted to open-ended search for the plant. Also GP is applied to represent the controller with a unified method. The formulations of simultaneous plant-controller design optimization problem and the description of solution techniques based on bond graph are derived. A feasible solutions for a plant/controller design using the simultaneous optimization methodology is illustrated.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.191-196
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• 2008

This paper presents an evolutionary algorithm for goal programming with preemptive priority. To do this, an evolutionary strategy is suggested which search for the solution satisfying the goals in the order of the priority. Two-sided assembly line balancing problems with multiple goals are used to validate the applicability of the algorithm. In the problems, three goals are considered in the following priority order: minimizing the number of mated-stations, achieving the goal level of workload smoothness, and maximizing the work relatedness. The proper evolutionary components such as encoding and decoding method, evaluation scheme, and genetic operators, which are specific to the problem being solved, are designed in order to improve the algorithm's performance. The computational result is reported.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.714-716
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• 1996

This paper presents an optimization method for optimal reactive power dispatch which minimizes real power loss and improves voltage profile of power systems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP). and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods were applied to the IEEE 30-bus system. Each simulation result, compared with that obtained by using a conventional gradient-based optimization method, Sequential Quadratic Programming (SQP), shows the possibility of applications of evolutionary computation to large scale power systems.