• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.921-934
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• 2014

The purpose of the study is to derive a long term reservoir operation method that is easy to understand and apply to practical use for dam operators. The zone based operation rule is a simple method to make operation decisions by criteria corresponding to storage zones. The reservoir storage levels dividing a reservoir, however, must be determined by some methods. We developed a reservoir operation model based on the zone based operation rule and the shuffled complex evolution algorithm (SCE-UA) was used to determine storage levels for zone division. The model was applied to Angat Dam in the Philippines that has trouble in water supply due to imbalance between supply and demand. We derived a zone based operation rule for Angat Dam and applied it to the reservoir simulation of Angat Dam using the historical inflow. The simulation results showed water supply deficit and power generation were improved by 34.5% and 21.2%, respectively, when compared with the historical records. The current study results may be used to derive a long term reservoir operation rule.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.218-219
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• 2011

This paper focuses on dispatching strategy for AGVs(Automated Guided Vehicle). The goal of AGV dispatching problem is allocating jobs to AGVs to minimizing QC delay and AGV total travel distance. Due to the highly dynamic nature of container terminal environment, the effect of dispatching is hard to predict thus it leads to frequent modification of dispatching results. Given this situation, single rule-based approach is widely used due to its simplicity and small computational cost. However, single rule-based approach has a limitation that cannot guarantee a satisfactory performance for the various performance measures. In this paper, dispatching strategy based on multicriteria heuristics is proposed. Proposed strategy consists of multiple decision criteria. A muti-objective evolutionary algorithm is applied to optimize weights of those criteria. The result of simulation experiment shows that the proposed approach outperforms single rule-based dispatching approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2514-2520
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• 2010

The objective of this paper is to propose the methodology for automated generation of the optimal security defense strategies using evolutionary techniques. As damages by penetration exploiting vulnerability in computer systems and networks are increasing, security techniques have been researched actively. However it is difficult to generate optimal defense strategies because it needs to consider various situations on network environment according to countermeasures. Thus we have adopted a genetic algorithm in order to generate an optimal defense strategy as combination of countermeasures. We have represented gene information with countermeasures. And by using simulation technique, we have evaluated fitness through evaluating the vulnerability of system having applied various countermeasures. Finally, we have examined the feasibility by experiments on the system implemented by proposed method.

• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.171-179
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• 2007

The greenhouse discrete optimum design program was developed using discrete optimum algorithm based on the genetic algorithm. The basic search method for the optimum design is the genetic algorithm, which is known to be very efficient for discrete optimization. In this paper, the objective function was the weight of the greenhouse structures and the constraints were the limits state design method. The design variables were galvanized steel pipes for plastic housing KSD 3760. Objective criteria were presented for the design of economic greenhouse structure and evaluation of its stability. The standardizations of greenhouse structure were used, as well as the normalization of greenhouse-related materials. Design examples were given to show the applicability of the optimum design using the discrete optimum algorithm based on the genetic algorithm of this study.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.681-695
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• 2019

A Transient Storage Model (TSM) is one of the most widely used model accounting for complex solute transport in natural river to understanding natural river properties with four TSM key parameters. The TSM parameters are estimated via inverse modeling. Parameter estimation of the TSM is carried out by solving optimization problem about finding best fitted simulation curve with measured curve obtained from tracer test. Several studies have reported uncertainty in parameter estimation from non-convexity of the problem. In this study, we assessed best combination of optimization method and objective function for TSM parameter estimation using Cheong-mi Creek tracer test data. In order to find best optimization setting guaranteeing convergence and speed, Evolutionary Algorithm (EA) based global optimization methods, such as CCE of SCE-UA and MCCE of SP-UCI, and error based objective functions were compared, using Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL). Overall results showed that multi-EA SC-SAHEL with Percent Mean Squared Error (PMSE) objective function is the best optimization setting which is fastest and stable method in convergence.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.910-911
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• 2011

미래사회의 기술적 혁신을 이끌 것으로 생각되는 로봇산업에 대한 관심이 증대되고 있으며, 최근에 많은 기술 개발과 개선이 이루어지고 있다. 이러한 경향은 점차 확대될 것으로 예상되며 전기자동차와 유사한 신성장 동력으로 성장할 것이다. 그러나, 로봇의 핵심 부품인 모터와 같은 구동계는 타분야에 비하여 기술적 혁신 및 관심을 끌지 못하고 있다. 앞으로 로봇산업이 확대 성장하여 산업용 로봇에서 가정용 로봇으로 진화하고, 로봇의 기능적인 측면이 보행, 러닝, 점프 등의 고성능을 구현하기 위해서는 각종 관절을 구동하는 역할을 담당하는 모터 및 동력전달 알고리즘의 연구 개발이 더욱 활발히 이루어져야 할 것이다. 특히, 인간과 유사한 로봇을 구현하기 우하여 보다 Flat하고 가볍고 출력밀도가 높은 새로운 구동장치의 필요성이 증대될 것이다. 본 논문에서는 산업노동지원을 위한 착용식 근력증강 로봇에 적용하는 모터 개발을 목적으로 적합한 구동계 타입을 선정하고, 요구 성능을 만족하는 전동기를 전자계 해석을 통하여 설계하고, 시작품 제작 및 평가를 통하여 해석결과를 검증하였다.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.52-54
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• 2004

압전 외팔보의 구조가 갈수록 복잡해짐에 따라 더 정확하고 효과적인 압전체의 해석이 요구되어지고 있다. 본 논문에서는 3차원 직육면체요소를 이용한 유한요소법을 통해 압전 변환기를 해석하고, 이것을 실험적으로 검증함으로써, 3차원 유한요소법을 이용한 해석 프로그램의 타당성을 확인하였다. 또한 3차원 유한요소법을 이용해서 압전 외팔보를 해석하고, 이것을 실험결과를 통해서 검증하였다. 그리고 압전 외팔보를 팬으로 적용하기 위해서 끝단에서의 최대 변위를 목적함수로 한 진화 전략 알고리즘을 적용하였다. 이를 통해서 팬용 압전 외팔보의 최적 설계를 수행하였다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.816-817
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• 2015

본 논문에서는 매입형 영구자석 전동기의 코깅토크 저감을 위해 회전자 표면에 노치를 적용하여 최적 설계를 수행하였다. 최적 설계를 위해 전역 최적점의 빠른 탐색이 가능한 크리깅 근사모델을 이용한 진화전략 알고리즘이 사용되었다. 설계 변수인 노치 크기에 대해 코깅 토크를 목적 함수로 두고 최적 설계를 진행하였으며, 이를 통해 찾은 전역 최적점과 지역 최적점 가운데 역기전력 특성을 고려하여 최종 설계안을 도출하였다.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.6
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• pp.305-311
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• 2000

This paper presents a hybrid algorithm for solving optimal power flow(OPF) in order to enhance a systems capability to cope with outages, which is based on combined application of evolutionary computation and local search method. The efficient algorithm combining main advantages of two methods is as follows : Firstly, evolutionary computation is used to perform global exploitation among a population. This gives a good initial point of conventional method. Then, local methods are used to perform local exploitation. The hybrid approach often outperforms either method operating alone and reduces the total computation time. The objective function of the security constrained OPF is the minimization of generation fuel costs and real power losses. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). In OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The method proposed is applied to IEEE 30 buses system to show its effectiveness.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.12
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• pp.1513-1519
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• 2013

A genetic algorithm (GA) is an optimization technique based on natural evolution theory to find the global optimal solution. Unlike the gradient-based method, it can design nanoscale structures in the electric field because it does not require sensitivity calculation. This research intends to design a nanoaperture with an unprecedented shape by the topology optimization scheme based on the GA and ON/OFF method in the visible frequency range. This research mainly aims to maximize the transmission rate at a measuring area located 10nm under the exit plane and to minimize the electric distribution at other locations. The finite element analysis (FEA) and optimization process are performed by using the commercial package COMSOL combined with the Matlab programming. The final results of the optimized model are analyzed by a comparison of the electric field intensity and the spot size of near field with those of the initial model.