• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.127-129
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• 2007

최적조류계산(Optimal Power Flow:OPF)은 전력계통에서 여러 가지 제약 조건을 만족하면서 경제적이고 안전하게 계통을 운영하기 위한 기법이다. 종래의 계산방법에는 비선형 계획법, 선형계획법 같은 수치해석적인 방법을 사용하였다. 그러나, 이러한 방법들은 전역 최저해를 구하기 위해서는 목적함수가 convex해야 한다. 또한, 계통 규모가 클 경우, 최적해 수렴이 안 되거나 수렴이 되더라도 시간이 많이 걸리는 단점이 있다. 최근에는 이러한 문제를 극복하고자 여러 가지 진화연산기법들이 최석조류계산 문제에 적용되고 있다. 본 논문에서 최근에 등장한 PSO알고리즘을 수정한 MPSO알고리즘은 이용한 최적조류계산 기법을 소개하고, 제안한 방법의 유용성을 보이기 위하여 IEEE 30,118 모선 계통의 최적 조류계산 문제에 적용하였다.

• Korean Journal of Optics and Photonics
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• v.8 no.2
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• pp.88-94
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• 1997

Photographic lenses and an aspheric optical pickup-lens are designed by using damped least-squares(DLS) method. We start optimization with arbitrary initial damping factor. To improve the rate of convergence and the stability in optimization, we apply the special procedure that estimates numerical adequacy of derivative increments of variables to the DLS method. When the initial damping factor is almost equal to the median of series of eigenvalues, the convergence and the stability of the method significantly are improved. Optimized lenses have the performance of each target.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.2
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• pp.21-31
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• 1999

This paper presents a new possibility of calculating optimal control for large scale which consist of non-linear dynamic sub-systems using two level hierarchical structures method. And the proposed method is based on the idea of block pulse transformation to simplify the algorithm and its calculation. This algorithm used an expansion around the equilibrium point of the system to fix the second and higher order terms. These terms are compensated for iteratively at the second level by providing a prediction for the states and controls which form of a part of the higher order terms. In this new approach the quadratic penalty terms are not used in the cost function. This allows convergence over a longer time horizon and also provides faster convergence. And the method is applied to the problem of optimization of the synchronous machine. Results show that the new approach is superior to conventional numerical method or other previous algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.353-355
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• 2003

본 논문은 유전자 알고리즘의 다양성(diversity)을 유지하면서 동시에 수렴(convergence) 속도를 향상시키기 위한 새로운 선택기법을 제안한다. 이를 위해 적합도가 높은 염색체를 다음 세대로 전달하면서 동시에 적합도가 낮은 염색체에 대해서도 일정 수준 전달되게 하였다. 또한 기존의 설러 선택기법 중 가장 일반적으로 사용되는 토너먼트 선택 기법의 문제점을 고찰하고, 제안 알고리즘의 최적도 밀 수렴속도를 모의 실험을 통해 비교 및 분석한다. 실험 결과로부터 제안 알고리즘은 기존의 토너먼트 선택기법에 비해 우수함을 확인하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.121-125
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• 1994

본 논문에서는 Hu에 의해 고안된 random 탐색법과 조합된 tabu 탐색법(radnom tabu 탐색법)을 결합계수를 구하는 학습 알고리즘으로 직접 사용하여 국소적 최적해에 수렴하는 것을 방지하고, 수렴정도를 개선하는 새로운 방법을 제안한다. 이 방법을 배타적 논리합 문제에 적용하여 역전파법 및 tabu 탐색법을 이용한 오차역전파법과 비교한다. 그리고, 각 파라메터가 오차함수의 수렴에 미치는 영향을 조사한다.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.121-131
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• 1998

이 논문의 목적은 비모수 회귀모형에 있어서의 오차의 분산을 추정하는 방법들 중 차분에 기저한 방법 (difference-based methods)을 이용한 기존의 추정량들을 비교 분석하는데 있다. 특히 점근적인 최적 이차 차분에 기저한 Hall과 Kay, Titterington(1990)의 HKT 추정량에 대한 그들의 추정량에 대한 문제점들을 제시하고, HKT추정량과, GSJS추정량, Rice추정량에 대하여 모의 실험을 이용하여 모수에 대한 수렴 속도를 비교 분석 하였다. 또한 GSJS 추정량에 대한 일치성과 수렴 속도를 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.467-478
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• 2016

In this paper, we try to find the optimal locations of NeNB(Nomadic evolved NodeB)s for maximizing the overall throughput of the PS-LTE networks. Since finding optimal locations of all NeNBs in a given area is NP-hard(Non-deterministic Polynomial time-hard) problem, we proposed a PSO-based heuristic approach. In order to evaluate the performance, we conducted two experiments. We compared performance with other schemes such as Exhaustive Search, Random Walk Search, and locating neighboring NeNBs with the same NeNB-to-NeNB distance. The proposed method showed the similar results to the exhaustive search method in terms of locating optimal position and user's data throughput. The proposed method, however, has the fast and consistent convergence time.

• Journal of Korean Society of Steel Construction
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• v.12 no.6
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• pp.629-638
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• 2000

With the positive features of simulated annealing algorithms such as simplicity of the algorithm and the possibility of finding global optimum solution, SA algorithm has been widely applied to structural optimization problems. However, the algorithms are far from practical applications in structural design or optimization of building structures due to requirement of a large number of iterations and dependency on cooling schedule and stopping criteria. In this paper, with the modification of annealing process and stopping criteria, a MSA algorithm is presented in the form of two phase annealing process for optimal seismic design of braced structures. The performance of the proposed algorithm has been illustrated in detail.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.682-685
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• 2014

In this paper, an improved designed of the circularly polarization antenna for sensor node. Stochastic optimization algorithms of Particle Swarm Optimization (PSO) and Adaptive Particle Swam Optimization(APSO) are studied and compared. To verify that the APSO is working better than the standard PSO, the design of a circularly polarization antenna is shows the optimized result with 27 iterations in the APSO and 41 iterations in th PSO.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.54-61
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• 2012

This paper proposes a fusion method of the queen-bee evolution into the rank-based control of mutation probability for improving the performances of genetic algorithms. The rank-based control of mutation probability which showed some performance improvements than the original method was a method that prevented individuals of genetic algorithms from falling into local optimum areas and also made it possible for the individuals to get out of the local optimum areas if they fell into there. This method, however, showed not good performances at the optimization problems that had a global optimum located in a small area regardless of the number of local optimum areas. We think that this is because the method is insufficient in the convergence into the global optimum, so propose a fusion method of the queen-bee evolution into this method in this paper. The queen-bee evolution inspired by reproduction process of queen-bee is a method that can strengthen the convergency of genetic algorithms. From the extensive experiments with four function optimization problems in order to measure the performances of proposed method we could find that the performances of proposed method was considerably good at the optimization problems whose global optimum is located in a small area as we expected. Our method, however, showed not good performances at the problems whose global optima were distributed in broad ranges and even showed bad performances at the problems whose global optima were located far away. These results indicate that our method can be effectively used at the problems whose global optimum is located in a small area.