• 디지털융복합연구
• /
• 제14권8호
• /
• pp.293-303
• /
• 2016

근래에 진화 연산을 활용한 교섭 게임의 분석은 게임 이론 분야에서 중요한 문제로 다루어지고 있다. 본 논문은 교섭 게임에서 진화 연산을 사용하여 이기종 인공 에이전트 간의 상호 작용 및 공진화 과정을 조사하였다. 교섭게임에 참여하는 진화전략 에이전트들로서 유전자 알고리즘(GA), 입자군집최적화(PSO) 및 차분진화알고리즘(DE) 3종류를 사용하였다. GA-agent, PSO-agent 및 DE-agent의 3가지 인공 에이전트들 간의 공진화 실험을 통해 교섭게임에서 가장 성능이 우수한 진화 계산 에이전트가 무엇인지 관찰 실험하였다. 시뮬레이션 실험결과, PSO-agent가 가장 성능이 우수하고 그 다음이 GA-agent이며 DE-agent가 가장 성능이 좋지 않다는 것을 확인하였다. PSO-agent가 교섭 게임에서 성능이 가장 우수한 이유를 이해하기 위해서 게임 완료 후 인공 에이전트 전략들을 관찰하였다. PSO-agent는 거래 실패로 인해 보수를 얻지 못하는 것을 감수하고서라도 가급적 많은 보수를 얻기 위한 방향으로 진화하였다는 것을 확인하였으며, 반면에 GA-agent와 DE-agent는 소량의 보수를 얻더라도 거래를 성공시키는 방향으로 진화하였다는 것을 확인하였다.

• 정보과학회 논문지
• /
• 제41권12호
• /
• pp.1090-1098
• /
• 2014

이 연구는 단봉 전역 최적화 성능이 개선된 적응적 코시 분포 차분 진화 알고리즘을 제안한다. 기존 적응적 코시 분포 차분 진화 알고리즘은(ACDE) 개체의 다양성을 보장하여 다봉 전역 최적화 문제에 우수한 "DE/rand/1" 돌연변이 전략을 사용했다. 그러나 이 돌연변이 전략은 수렴 속도가 느려 단봉 전역 최적화 문제에 단점이 있다. 제안 알고리즘은 "DE/rand/1" 돌연변이 전략 대신 수렴 속도가 빠른 "DE/current-to-best/1" 돌연변이 전략을 사용했다. 이때, 개체의 다양성이 부족하여 발생할 수 있는 지역 최적해로의 수렴을 방지하기 위해서 매개변수 초기화 연산이 추가됐다. 매개변수 초기화 연산은 특정세대를 주기로 실행되거나 또는 선택 연산에서 모든 개체가 진화에 실패하는 경우 실행된다. 매개변수 초기화 연산은 각 개체들의 매개변수에 탐험적 특성이 높은 값을 할당하여 넓은 공간을 탐색할 수 있도록 보장한다. 성능 평가 결과, 개선된 적응적 코시 분포 차분 진화 알고리즘이 최신 차분 진화 알고리즘들에 비해 특히, 단봉 전역 최적화 문제에서 성능이 개선됨을 확인했다.

• Journal of Electrical Engineering and Technology
• /
• 제1권4호
• /
• pp.435-447
• /
• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• 한국지능시스템학회논문지
• /
• 제17권5호
• /
• pp.591-597
• /
• 2007

군집 로봇시스템에서 개개의 로봇은 스스로 주위의 환경과 자신의 상태를 스스로 판단하여 행동하고, 필요에 따라서는 다른 로봇과 협조를 통하여 어떤 주어진 일을 수행할 수 있어야 한다. 따라서 개개의 로봇은 동적으로 변화하는 환경에 잘 적응할 수 있는 학습과 진화능력을 갖는 것이 필수적이다 이를 위하여 본 논문에서는 새로운 Polygon 기반의 Q-learning 알고리즘과 분산유전알고리즘을 이용한 새로운 자율이동로봇의 행동학습 및 진화방법을 제안한다. 또한 개개의 로봇이 통신을 통하여 염색체를 교환하는 분산유전알고리즘은 각기 다른 환경에서 학습한 우수한 염색체로부터 자신의 능력을 향상시킨다. 특히 본 논문에서는 진화의 성능을 향상시키기 위하여 강화학습의 특성을 이용한 선택 교배방법을 채택하였다. 제안된 방법은 협조탐색 문제에 적용하여 컴퓨터 모의실험을 통하여 그 유효성을 검증한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권4호
• /
• pp.1757-1772
• /
• 2020

As the smartphone market becomes saturated, an innovative device equipped with new features is expected to appear soon in mobile communications. In particular, various possibilities were raised regarding the alternative technologies that can develop post-smartphones, which are differentiated from the current smartphones, as Korea commercialized the 5G infrastructure for the first time in the world. Under these circumstances, the Korean government announced the "5G+ Strategy for Realizing Innovative Growth" in April 2019, vowing to build an innovative industrial ecosystem quickly while creating various convergence services based on the 5G infrastructure. As described above, the policy importance of the alternative technologies that will develop post-smartphones is increasing, but the theoretical study on the technology evolution of post-smartphones has not been systematically conducted until now. This study reviewed the alternative technologies that can develop post-smartphones through documentary research, and data mining analysis was performed on the research result using actual data. The policy priority was also set quantitatively for the alternative technologies of post-smartphones in order to determine the alternative post-smartphone technology that the government should focus on given the constraint of limited resources. As a results, autonomous vehicle(43.68%) was found to be most important, followed by artificial intelligence(17.4%) and Internet of Things(13.1%), among alternative technologies that could develop into the post-smartphone.

• Industrial Engineering and Management Systems
• /
• 제14권3호
• /
• pp.299-311
• /
• 2015

Nowadays, the distribution centres aim to reduce costs by reducing inventory and timely shipment. Cross docking is a logistics strategy in which products delivered to a distribution centre by inbound trucks are directly unloaded and transferred to outbound trucks with minimum warehouse storage. Moreover, on-time delivery in a distribution network becomes very crucial especially when several distribution centres and customers are involved. Therefore, an efficient truck scheduling is needed to synchronize the delivery throughout the network in order to satisfy all stake-holders. This paper presents a mathematical model of a mixed integer programming for door assignment and truck scheduling in a multiple inbound and outbound doors cross docking problem according to Just-In-Time concept. The objective is to find the schedule of transhipment operations to simultaneously minimize the total earliness and total tardiness of trucks. Then, a multi-objective differential evolution (MODE) is proposed with an encoding scheme and four decoding strategies, called ITSH, ITDD, OTSH and OTDD, to find a Pareto frontier for the multi-door cross docking problems. The performances of MODE are evaluated using 15 generated instances. The numerical experiments demonstrate that the proposed algorithm is capable of finding a set of diverse and high quality non-dominated solutions.

• Smart Structures and Systems
• /
• 제14권1호
• /
• pp.17-37
• /
• 2014

In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the $({\mu}/{\rho}+{\lambda})-{\sigma}$-SA-ES, (iii) the $({\mu}_I,{\lambda})-{\sigma}$-SA-ES, and (iv) the (${\mu}_w,{\lambda}$)-CMA-ES. The study is based on a six-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-space estimation problem and deserve further attention.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권12호
• /
• pp.5972-5989
• /
• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• 한국데이타베이스학회:학술대회논문집
• /
• 한국데이타베이스학회 2008년도 연합학회학술대회
• /
• pp.13-30
• /
• 2008

본 연구의 목적은 지식기반관점에서 인터넷 포탈에서의 지식공유 유형을 분석하는 것이다. 또한 사용자의 지식공유 행태를 고찰함으로써 인터넷 포탈의 진화과정에 대한 통찰을 얻고자 하는 것이다. 이를 위해 먼저 지식공여와 지식수집이라는 2가지 차원을 기반으로 지식공유 유형을 제시하고, 한국의 주요한 인터넷 포탈에 대한 사례분석을 통하여 제시한 유형을 검증하였다. 연구의 결과에서 협업, 축적 및 출판이라는 3가지 유형의 인터넷 포털 지식공유 유형이 도출되었다. 또한 사용자의 지식공유 행태는 인터넷 포탈 진화과정의 주요동인으로서 작용한다는 것을 제시하였다.

• Coupled systems mechanics
• /
• 제3권1호
• /
• pp.1-25
• /
• 2014

In this work, we present the theoretical formulation, operator split solution procedure and partitioned software development for the coupled thermomechanical systems. We consider the general case with nonlinear evolution for each sub-system (either mechanical or thermal) with dedicated time integration scheme for each sub-system. We provide the condition that guarantees the stability of such an operator split solution procedure for fully nonlinear evolution of coupled thermomechanical system. We show that the proposed solution procedure can accommodate different evolution time-scale for different sub-systems, and allow for different time steps for the corresponding integration scheme. We also show that such an approach is perfectly suitable for parallel computations. Several numerical simulations are presented in order to illustrate very satisfying performance of the proposed solution procedure and confirm the theoretical speed-up of parallel computations, which follow from the adequate choice of the time step for each sub-problem. This work confirms that one can make the most appropriate selection of the time step with respect to the characteristic time-scale, carry out the separate computations for each sub-system, and then enforce the coupling to preserve the stability of the operator split computations. The software development strategy of direct linking the (existing) codes for each sub-system via Component Template Library (CTL) is shown to be perfectly suitable for the proposed approach.