• 한국공간구조학회논문집
• /
• 제2권3호
• /
• pp.61-70
• /
• 2002

The objective of this study is the development of a size and shape discrete optimum design algorithms, which is based on the genetic algorithms and the fuzzy theory. This algorithms can perform both size and shape optimum designs of plane and space trusses. The developed fuzzy shape-GAs (FS-GAs) was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. This study solves the problem by introducing the FS-GAs operators into the genetic.

• International Journal of Aeronautical and Space Sciences
• /
• 제18권4호
• /
• pp.729-739
• /
• 2017

The objective of this study was to optimize minimum-energy impulsive spacecraft intercept using genetic algorithms. A mathematical model was established on two-body system based on f and g solution and universal variable to address spacecraft intercept problem for non-coplanar elliptical orbits. This nonlinear problem includes many local optima due to discontinuity and strong nonlinearity. In addition, since it does not provide a closed-form solution, it must be solved using a numerical method. Therefore, the initial guess is that a very sensitive factor is needed to obtain globally optimal values. Genetic algorithms are effective for solving these kinds of optimization problems due to inherent properties of random search algorithms. The main goal of this paper was to find minimum energy solution for orbit transfer problem. The numerical solution using initial values evaluated by the genetic algorithm matched with results of Hohmann transfer. Such optimal solution for unrestricted arbitrary elliptic orbits using universal variables provides flexibility to solve orbit transfer problems.

• Structural Engineering and Mechanics
• /
• 제64권5호
• /
• pp.579-589
• /
• 2017

This paper deals with the optimum cost design of partially prestressed concrete I crosssectioned beams by using Genetic Algorithms. For this purpose, the optimum cost design of two selected example problems that have different characteristics in behavior are performed via Genetic Algorithms by determining their objective functions, design variables and constraints. The results obtained from the technical literature are compared with the ones obtained from this study. The interpretation of the results show that the design of partially prestressed concrete I crossectioned beams from cost point of view by using Genetic Algorithms is 35~50 % more economical than the traditional ones (technical literature) without conceding safety.

• Journal of Advanced Marine Engineering and Technology
• /
• 제20권2호
• /
• pp.108-108
• /
• 1996

This paper describes a new approach to solve balancing of a rigid rotor. In this paper, the balancing of the rigid rotor using genetic algorithms, which are search algorithms based on the mechanics of natural selection and natural genetics is proposed. Under the assumption that the initial vibration values used to calculate correction masses contain errors, the influence coefficient method, the least squares method and a genetic algorithm are compared. The results show that the vibration amplitude obtained with the least squares method and the genetic algorithm is smaller than that obtained with the influence coefficient method.

• Journal of Advanced Marine Engineering and Technology
• /
• 제20권2호
• /
• pp.40-47
• /
• 1996

This paper describes a new approach to solve balancing of a rigid rotor. In this paper, the balancing of the rigid rotor using genetic algorithms, which are search algorithms based on the mechanics of natural selection and natural genetics is proposed. Under the assumption that the initial vibration values used to calculate correction masses contain errors, the influence coefficient method, the least squares method and a genetic algorithm are compared. The results show that the vibration amplitude obtained with the least squares method and the genetic algorithm is smaller than that obtained with the influence coefficient method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.140-140
• /
• 2000

Traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain. Hybridizing a genetic algorithm with other algorithms can produce better performance than both the genetic algorithm and the other algorithms. In this paper, we use random process and simulated annealing instead of mutation operator in order to get well tuned fuzzy rules. The key of this approach is to adjust both the width and the center of membership functions so that the tuned rule-based fuzzy controller can generate the desired performance. The effectiveness of the proposed algorithm is verified by computer simulation.

• Journal of international Conference on Electrical Machines and Systems
• /
• 제1권1호
• /
• pp.135-142
• /
• 2012

In this paper, optimal selection of the unified power flow controller (UPFC) damping controller parameters in order to improve the power system dynamic response and its stability based on two modified intelligent algorithms have been proposed. These algorithms are based on a modified intelligent particle swarm optimization (PSO) and continuous genetic algorithm (GA). After extraction of UPFC dynamic model, intelligent PSO and genetic algorithms are used to select the effective feedback signal of the damping controller; then, to compare the performance of the proposed UPFC controller in damping the critical modes of a single-machine infinite-bus (SMIB) power system, the simulation results are presented. The comparison shows the good performance of both presented PSO and genetic algorithms in an optimal selection of UPFC damping controller parameters and damping oscillations.

• 대한교통학회지
• /
• 제22권2호
• /
• pp.43-54
• /
• 2004

본 연구에서는 인공지능(Artificial Intelligence)방법 중의 하나인 유전자 알고리즘(Genetic Algorithm)을 도로선형최적화 모형개발의 탐색엔진으로 활용하기 위한 핵심도구인 유전자 연산자(Genetic Operator)의 개발과 적용과정을 통해 그 특징과 유용성을 제시하였다. 균일돌연변이 연산자, 직선돌연변이 연산자. 비균일 돌연변이 연산자, 전체 비균일 돌연변이 연산자 등 4개의 돌연변이 연산자가 탐색영역(Search space)의 가능한 모든 부분을 탐험(Exploration)하기 위해 적용되었으며, 단순교차 연산자, 두 개의 점을 이용한 교차 연산자, 산술교차 연산자, 학습교차 연산자 등 4개의 교차 연산자가 노선대안의 우수한 유전형질을 다음세대에 효과적으로 전달(Exploitation)하기 위해 시험되었다. 사례연구와 민감도 분석과정을 통해 유전자 알고리즘 및 개발 적용된 8개 유전자 연산자의 도로선형최적화과정 도입이 우수한 노선대안을 빠르고 효과적으로 탐색함을 알 수 있었으며, 돌연변이 연산자와 교차 연산자의 효과적 조합이 상호보완기능을 통해 탐색능력의 향상에 큰 영향을 끼치는 것으로 파악되었다. 또한, 개발 적용된 연산자 이외에도 새로운 연산자의 개발 가능성이 무한하며, 이는 도로선형최적화에 유전자 알고리즘의 적용이 타당함을 반증함도 주목할 만하다.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제34권11호
• /
• pp.971-983
• /
• 2007

셀룰러 유전알고리즘(CGAs)은 모집단이 특정한 위상 구조를 갖는 유전알고리즘의 일종이다. 보통의 경우, CGAs의 모집단 공간은 네트워크 이론 측면에서 상대적으로 긴 평균경로길이와 큰 클러스터링계수를 갖는 정규 격자형 위상 구조이다. 평균경로길이가 길면 멀리 떨어진 개체들 사이의 유전적 상호작용이 느리게 일어난다. 따라서 클러스터링계수를 유지하면서 평균경로길이를 줄인다면 개체의 다양성이 유지되면서도 모집단이 보다 빠르게 수렴할 것이다. 이 논문에서는 최소좁은세상 셀룰러 유전알고리즘(SSWCGAs)을 제안한다. SSWCGAs에서 각 개체는 클러스터링이 잘되었으면서도 노드를 연결하는 평균경로길이가 짧은 모집단에 거주하여, 클러스터링에 의한 세부탐색 능력을 유지하면서도 전역탐색을 잘하게 된다. 네 가지 실변수 함수와 두 가지 GA-hard 문제에 대한 실험을 통하여 SSWCGAs가 SGAs 및 CGAs보다 효과적임을 보였다.

• 제어로봇시스템학회논문지
• /
• 제17권7호
• /
• pp.619-624
• /
• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.