• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.247-257
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• 2005

Generally, the network topology design problem is characterized as a kind of NP-hard combinatorial optimization problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size. In this paper, we propose the efficient approach with two phase that is comprised of evolutionary computation approach based on Prufer number(PN), which can efficiently represent the spanning tree, and a heuristic method considering 2-connectivity, to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability: firstly, to find the spanning tree, genetic algorithm that is the most widely known type of evolutionary computation approach, is used; secondly, a heuristic method is employed, in order to search the optimal network topology based on the spanning tree obtained in the first Phase, considering 2-connectivity. Lastly, the performance of our approach is provided from the results of numerical examples.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.10-19
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• 2008

This study designed and implemented a J2ME based on mapping viewer to browse the SVG based wireless-map in mobile phone. This proposed technique was efficiently applied to a forest fire extinguishment information management system by mapping the exact location of important objects on wireless-map in wireless network. As the result, the study helps to guide the safe and efficient extinguishment affairs and provides the safe extinguishment environment for ground fire fighting teams in real time. And also this technique presents the way to move the client mapping function such as representation of the moving coordinates to server and made it possible to operate SVG based viewer in personal cellular phone.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.40-50
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• 2009

Incorrect deployment of RFID readers occurs reader-to-reader interferences in many applications using RFID technologies. Reader-to-reader interference occurs when a reader transmits a signal that interferes with the operation of another reader, thus preventing the second reader from communicating with tags in its interrogation zone. Interference detected by one reader and caused by another reader is referred to as a reader collision. In RFID systems, the reader collision problem is considered to be the bottleneck for the system throughput and reading efficiency. In this paper, we propose a novel RFID reader anti-collision algorithm based on evolutionary algorithm(EA). First, we analyze characteristics of RFID antennas and build database. Also, we propose EA encoding algorithm, fitness algorithm and genetic operators to deploy antennas efficiently. To show superiority of our proposed algorithm, we simulated our proposed algorithm. In the result, our proposed algorithm obtains 95.45% coverage rate and 10.29% interference rate after about 100 generations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.352-362
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• 2010

The simultaneous operation of multiple UAV's makes it possible to enhance the mission accomplishment efficiency. In order to achieve this, easily scalable control algorithms are required, and swarm intelligence having such characteristics as flexibility, robustness, decentralized control, and self-organization based on behavioral model comes into the spotlight as a practical substitute. Recently, evolutionary robotics is applied to the control of UAV's to overcome the weakness of difficulties in the logical design of behavioral rules. In this paper, a neural network controller evolved by evolutionary robotics is applied to the control of multiple UAV's which have the mission of searching limited area. Several numerical demonstrations show the proposed algorithm has superior results to those of behavior based neural network controller which is designed by intuition.

• Journal of KIISE
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• v.43 no.2
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• pp.204-211
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• 2016

In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that can be controlled by a user setting parameters. In the melody generation part, we designed new fitness functions for melody based on harmony theory. We also designed evolutionary operators that are conducted by considering a musical context to improve computational efficiency. In the experiments, we compared four metaheuristics to optimize the rhythm fitness functions: Simple Genetic Algorithm (SGA), Elitism Genetic Algorithm (EGA), Differential Evolution (DE), and Particle Swarm Optimization (PSO). Furthermore, we compared proposed genetic algorithm for melody with the four algorithms for verifying performance. In addition, composition results are introduced and analyzed with respect to musical correctness.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.360-364
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• 2001

본 논문에서는 최근의 진화적 구조최적화(ESO) 전략을 회전축의 형상최적화에 적용하였으며, 각 계산 스텝마다 단위 유한요소의 크기를 변경함으로써 기존의 방법보다 빠르고 정확한 최적형상에 수렴하는 새로운 방법을 제시하였다. 축요소의 직경을 시스템 설계변수로 하였으며, 축중량의 감소, 공진배율(Q-factor)의 감소 및 충분한 위험속도의 분리여유를 갖도록 목적함수를 설정하였다. 불평형응답 및 굽힙응력의 구속조건을 부가하였으며, 목적함수에 대한 설계변수의 감도해석을 수행하였다. 전동기축계에 대한 적용 결과로부터 주파수와 동적 구속조건하의 로터베어링 시스템에 대한 축 형상 최적화에 ESO법이 효과적으로 이용될 수 있음을 확인하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.325-327
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• 2015

최근 국제적으로 e-Navigation이 추진되고 있으며, 이는 국제적으로 표준화된 정보 제공 및 결합을 통하여 해상에서 항해를 안전하고 효율적으로 하는데 목적이 있다. 그리고 국내에서는 자체적인 VTS 기술개발 시스템이 없어 외산장비를 구축 활용하여 왔으며, e-Navigation 진화, 장비간 연계 등에 어려움이 있어 왔다. 최근 국내에서도 VTS 시스템에 대한 국산화 기술개발이 진행되고 있으며, 시스템 기능개발을 어느 정도 완료하고 성능과 독자적인 기술개발을 고려하고 있다. 따라서 현재 국내에서 추진되고 있는 국산화 기술개발에 대한 현황을 확인하고 보완할 내용에 대하여도 검토하고자 한다. 특히 국산화 시스템은 e-Navigation 진화를 위한 기술적 내용을 포함하지 않아 향후 진화에 어려움이 있을 수 있으며, 외산장비와 국산화 장비 시스템간 정보교환 문제 또한 고려되어야 한다. 따라서 실제적 국제적인 VTS 고도화 시스템으로 진화하기 위해서는 시범 서비스를 통한 운용성 확보 그리고 시스템간 연동을 위한 추가설계와 구축시험 및 빅데이터 처리를 위하여는 센터간 연계 통합화 노력이 요구된다. 즉, 향후 국내의 VTS운용 시스템이 다양한 외산장비가 입찰에 낙찰되어 도입구축 운용되는 경우에도 같은 상황으로서 반드시 효율적인 연계 방안으로 수립되어야 한다. 이는 국가적으로도 VTS 시스템이 매우 중요하고 그 서비스의 안전성이 보장되어야 하며, e-Navigation 서비스 도입을 위하여 VTS 국산화 및 고도화가 반드시 고려되어야 한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1036-1041
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• 2006

본 연구에서는 허브와 스포크의 입지선정과 차량 경로가 통합된 hub-and-spoke 네트워크 설계문제를 다룬다. Hub-and-spoke 네트워크는 대량화와 공동화를 통해 물류효율화를 실현하기 위한 대표적인 구조로 물류시스템에서 흔히 사용되고 있다. 이러한 물류시스템에서 물류비용의 절감과 고객서비스 향상을 위한 효율적인 수송네트워크 설계는 매우 중요하다. 전통적인 hub-and-spoke 네트워크 설계문제에서 각 스포크의 위치와 화물량이 미리 주어진 상황에서 허브의 입지를 결정하였다. 하지만 스포크 역시 스포크가 담당하는 고객들의 위치와 담당 영역에 따라 그 위치와 수, 그리고 화물량이 변할 수 있다. 또한 정확한 비용산출을 위해서는 스포크에서 고객으로의 수집과 배달을 위한 차량경로가 함께 고려되어야 한다. 다루는 수송망 설계문제는 상호 관련성 있는 여러 부분문제가 결합된 통합문제로써 이를 해결하는 방법으로 기존의 발견적 방법에 의한 순차적 기법은 한계가 있다. 본 연구에서는 공생 진화알고리듬 기반의 방법론을 채용하여 다루는 수송망 설계문제를 동시에 통합적으로 해결할 수 있는 알고리듬을 개발한다. 실험을 통해 개발한 알고리듬의 우수성과 그 적용성을 보인다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.63-71
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• 2021

This paper propose an development of the unmanned automatic test system for a portable detector using TRIZ Methodology. A new development scheme among of the unmanned automatic test system configurations was obtained after application of the TESE(Trends of Engineering System Evolution) one of the TRIZ methods. Using Pugh matrix drives some improving ideas. The key idea of this unmanned automatic test system scheme is to minimize whole test procedure time of each portable detector and to maximize the amount of portable detectors at once. Between the before and the after configurations of the 3D mechanical model find out improvements. This paper shows that the proposed development scheme improves the test performance efficiency compared to previous scheme.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.29-37
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• 1999

In general, the information processing capability of a neural network is determined by its architecture and efficient training patterns. However, there is no systematic method for designing neural network and selecting effective training patterns. Evolutionary Algorithms(EAs) are referred to as the methods of population-based optimization. Therefore, EAs are considered as very efficient methods of optimal system design because they can provide much opportunity for obtaining the global optimal solution. In this paper, we propose a new method for finding the optimal structure of neural networks based on competitive co-evolution, which has two different populations. Each population is called the primary population and the secondary population respectively. The former is composed of the architecture of neural network and the latter is composed of training patterns. These two populations co-evolve competitively each other, that is, the training patterns will evolve to become more difficult for learning of neural networks and the architecture of neural networks will evolve to learn this patterns. This method prevents the system from the limitation of the performance by random design of neural networks and inadequate selection of training patterns. In co-evolutionary method, it is difficult to monitor the progress of co-evolution because the fitness of individuals varies dynamically. So, we also introduce the measurement method. The validity and effectiveness of the proposed method are inspected by applying it to the visual servoing of robot manipulators.