• 한국정보처리학회논문지
• /
• 제5권11호
• /
• pp.2897-2907
• /
• 1998

학습 예(training examples)로 부터 규칙을 생성하는 문제는 큰 탐색 공간상에서 많은 지역최소치를 가지고 있는 최적화 문제로 귀결되므로 복잡하고 어려운 문제로 알려져 있다. 이러한 생성규칙을 만들기 위한 여러 가지 학습방법들이 제안되었으며, 그 중 한가지 학습방법이 유전자알고리즘을 연산모델로 사용하는 것이다. 그러나 전통적인 유전자알고리즘은 전역해 부근에서 수렴속도가 떨어지고, 추출된 규칙의 효율성에 문제가 있다. 본 논문에서는 유전자알고리즘의 학습과정에서 포착되는 염색체의 스키마를 분석하여 탐색공간을 부분해(subsolution)를 구할 수 있는 공간들로 분할함으로써, 보다 일반화된 분류 규칙집합을 찾는 방법을 제안하였다. 또한, 실험을 통하여 기존의 기계학습 방법을 사용한 경우와 효율을 상호 비교하여 제안한 방법을 타당성을 입증하였다.

• Journal of Power Electronics
• /
• 제16권2호
• /
• pp.610-620
• /
• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.

• 한국측량학회지
• /
• 제24권5호
• /
• pp.425-431
• /
• 2006

최근 정부는 제4차 국토종합계획을 수정 보완하는 등 국토의 균형발전에 많은 노력을 경주하고 있다. 그러나, 기존 도로의 교통사고발생은 OECD 29개 국가 중 최하위권인 25위로 머물러있는 실정이다. 따라서 본 연구에서는 고속국도 및 국도 등에서 교통사고가 가장 많이 발생하고 있는 입체교차시설인 인터체인지 분기점의 기존 설계기준에 대한 문제점을 분석하여 적합한 설계속도를 제안하고자 한다. 그 결과로 교통사고를 미연에 방지하고 안전하고 쾌적한 도로조건 확보 및 교통용량의 극대화 등 도로기능을 극대화할 수 있는 유출입 접속부에서의 설계속도를 얻고자 한다.

• 한국항공우주학회지
• /
• 제44권7호
• /
• pp.620-628
• /
• 2016

호모토피 알고리즘은 비선형성이 강하거나 다수의 최적해가 존재하는 비선형 최적제어 문제에서 점진적으로 비선형 항으로 고려하게 해줌으로써 강건하게 전역의 최적해를 구할 수 있는 방법이다. 본 논문에서는 초기 추정치에 둔감한 SBS 알고리즘과 호모토피 알고리즘을 결합한 비선형 최적제어 알고리즘을 제시하였다. 이러한 접근방식은 저추력 궤적최적화 문제와 같이 비선형성이 강한 문제의 최적해를 구하는데 효과적이다. 또한, 비선형성이 강한 문제들은 종종 다수 국소 해가 존재하게 되는데, 이러한 경우에 SBS-호모토피 방법은 점진적으로 전역해를 찾는 것을 가능하게 한다.

• International Journal of Aeronautical and Space Sciences
• /
• 제14권4호
• /
• pp.324-333
• /
• 2013

The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm (GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem. In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method, were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization example and the results of the proposed method were compared with those of the traditional method using standard random initialization for the initial population of the GA.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권3호
• /
• pp.234-240
• /
• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• 대한산업공학회지
• /
• 제25권4호
• /
• pp.500-509
• /
• 1999

In this paper, we consider an optimal routing problem when point-to-point and point-to-multipoint connection traffics are offered in an ATM network. We propose a mathematical model for cost-minimizing configuration of a logical network for a given ATM-based BISDN. Our model is essentially identical to the previous one proposed by Kim(Kim, 1996) which finds a virtual-path configuration where the relevant gains obtainable from the ATM technology such as the statistical multiplexing gain and the switching/control cost-saving gain are optimally traded-off. Unlike the Kim's model, however, ours explicitly considers the VP's QoS(Quality of Service) for more efficient utilization of bandwidth. The problem is a large-scale, nonlinear, and mixed-integer problem. The proposed algorithm is based on the local linearization of equivalent-capacity functions and the relaxation of link capacity constraints. As a result, the problem can be decomposed into moderate-sized shortest path problems, Steiner arborescence problems, and LPs. This fact renders our algorithm a lot faster than the previous nonlinear programming algorithm while the solution quality is maintained, hence application to large-scale network problems.

• International Journal of Computer Science & Network Security
• /
• 제21권3호
• /
• pp.304-310
• /
• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권12호
• /
• pp.4617-4632
• /
• 2021

IEEE 802.11ax is a protocol being developed for high-density Wireless Local Area Networks (WLAN). Several algorithms have been proposed to improve the level of spatial reuse applied in IEEE 802.11ax. However, these algorithms are tentative and do not specify how to select the transmit power and carrier sense threshold in practice; It is unclear when and why the tuned parameters lead to better network performance. In this paper, we restricted the scale of transmit power tuning to prevent the case of backfire in which spatial reuse will result in transmission failure. If the restrictions cannot be satisfied, spatial reuse will be abandoned. This is why we named the proposed scheme as Arbitration based Spatial Reuse (ASR). We quantified the network performance after spatial reuse, and formulate a corresponding maximum problem whose solution is the optimal carrier sense threshold and transmit power. We verified our theoretical analysis by simulation and compared it with previous studies, and the results show that ASR improves the throughput up to 8.6% compared with 802.11ax. ASR can avoid failure of spatial reuse, while the spatial reuse failure rate of existing schemes can up to 36%. To use the ASR scheme in practice, we investigate the relation between the optimal carrier sense threshold and transmit power. Based on the relations got from ASR, the proposed Relation based Spatial Reuse (RSR) scheme can get a satisfactory performance by using only the interference perceived and the previously found relations.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
• /
• pp.359-366
• /
• 2005

Most engineering optimization are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithm, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search(HS) meta-heuristic algorithm-based approach for structural size optimization problems with continuous design variables. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. Two classical space truss optimization problems are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to structural engineering problems than those obtained using current algorithms.