• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.3 s.3
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• pp.73-82
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• 2001

This study examines the applicability of the Nash model and the Diskin model, which are linear and nonlinear runoff models, respectively, by applying optimization techniques to the parameter calibration of the two models. Nonlinear programming which is one of traditional optimization techniques and Genetic Algorithm which has been actively applied recently are used in this study. The Nash and Diskin models which use the calibrated parameter with a flood events are applied to a different flood event in Soyang Dam basin. The results obtained from the parameter calibration show slight discrepancy depending upon the flood events. It has been found in the comparion between the observed hydrograph and the hydrographs obtained from the parameter calibration that the Diskin model can better simulate the observed hydrograph than the Nash model can, especially, for the peak flow. This can be analyzed that the Diskin model which is a nonlinear runoff model is better off in simulating the nonlinear characteristic of the rainfall-runoff process.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.247-255
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• 2004

The majority of real-world problems encountered by engineers involve simultaneous optimization of competing objectives. In this case instead of single optima, there is a set of alternative trade-offs, generally known as Pareto-optimal solutions. The use of evolutionary algorithms Pareto GA, which was first introduced by Goldberg in 1989, has now become a sort of standard in solving Multiobjective Optimization Problems (MOPs). Though this approach was further developed leading to numerous applications, these applications are based on Pareto ranking and employ the use of the fitness sharing function to maintain diversity. Another scheme for solving MOPs has been presented by J. Nash to solve MOPs originated from Game Theory and Economics. Sefrioui introduced the Nash Genetic Algorithm in 1998. This approach combines genetic algorithms with Nash's idea. Another central achievement of Game Theory is the introduction of an Evolutionary Stable Strategy, introduced by Maynard Smith in 1982. In this paper, we will try to find ESS as a solution of MOPs using our game model based co-evolutionary algorithm. First, we will investigate the validity of our co-evolutionary approach to solve MOPs. That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP. Second, we will evaluate the effectiveness of our approach, comparing it with other methods through rigorous experiments on several MOPs.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.491-496
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• 2002

Multi-objective Optimization Problems(MOPs) are occur more frequently than generally thought when we try to solve engineering problems. In the real world, the majority cases of optimization problems are the problems composed of several competitive objective functions. In this paper, we introduce the definition of MOPs and several approaches to solve these problems. In the introduction, established optimization algorithms based on the concept of Pareto optimal solution are introduced. And contrary these algorithms, we introduce theoretical backgrounds of Nash Genetic Algorithm(Nash GA) and Evolutionary Stable Strategy(ESS), which is the basis of Co-evolutionary algorithm proposed in this paper. In the next chapter, we introduce the definitions of MOPs and Pareto optimal solution. And the architecture of Nash GA and Co-evolutionary algorithm for solving MOPs are following. Finally from the experimental results we confirm that two algorithms based on Evolutionary Game Theory(EGT) which are Nash GA and Co-evolutionary algorithm can search optimal solutions of MOPs.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.784-786
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• 2005

본 논문에서 대상으로 하는 네트워크 구조는 서비스 센터, 터미널(사용자), 그리고 연결 케이블로 이뤄져 있고 서비스 센터의 구성을 위한 의사 결정자와 서비스 일터와 사용자의 터미널을 연결하는 의사 결정자들이 존재하고 각자의 목적함수를 최적화 하기위해 비타협적으로 의사 결정과정에서 창설한다고 가정한다. 이러한 문제는 Nash 게임으로 정식화될 수 있다. 본 논문에서는 연결비용, 평균 메시지 지연, 네트워크 신뢰도를 고려하여, Nash 게임으로 정식화되는 광대역 통신 네트워크의 네트워크 토폴로지 설계 문제들을 풀기 위해 Nash 유전 알고리즘을 이용한다. 수치 실험을 통해 본 논문에서 이용한 Nash 유전 알고리즘이 효율적이여 효과적인 방법이라는 것을 살펴본다.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.93.3-93
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• 2002

$\textbullet$ Co-evolutionary algorithms $\textbullet$ Nash Genetic Algorithms $\textbullet$ Multi-objective Optimization $\textbullet$ Distance dependent mutation $\textbullet$ Pareto Optimality

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.1
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• pp.13-25
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• 1999

This paper presents a model of competitive positioning and pricing of new products in a multi-segmented market. The segments in the market are located on a multi-dimensional discrete attribute space with fixed demands. Firms launch products sequentially on the attribute space, incurring fixed and variable costs, and then decide on their product prices. Each firm acts to maximize its profit. Market share of a firm is determined by the position and price of Its product. We provide sufficient conditions for the existence and uniqueness of Nash equilibrium Another equilibrium concept is Introduced and related to the Nash equilibrium. A heuristic algorithm based on genetic algorithms is designed to obtain the Nash equilibrium.

• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.121-131
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• 2004

SIMHYD and TANK model are used to predict time series of daily rainfall-runoff of Soyang Dam and Youngcheon Dam watershed. The performances of SIMHYD model with 7 parameters and TANK model with17 parameters are compared. Three optimization methods (Genetic algorithm, Pattern search multi-start and Shuffled Complex Evolution algorithm) were applied to study-areas with 3 different types of objective functions. Efficiency of TANK model is higher than that of SIMHYD. Among different types of objective function, Nash-sutcliffe coefficient is found to be the most appropriateobjective function to evaluate applicability of model.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.159-165
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• 2014

Vegetative Filter Strip (VFS) is one of effective Best Management Practices (BMPs) to prevent sediment-laden water problem, is installed at the edge of source area such agricultural area so that sediment occurred in source area is trapped by VFS before it flow into stream or river. Appropriate scale of it needs to be simulated before it is installed, considering various field conditions. In this study, a model using VFSMOD-w model and Genetic Algorithm to determine effective VFS length was developed, it is available to calibrate input parameter related to source area sediment yield through thousands of VFSMOD-w simulations. Useful DBs, moreover, are stored in the model so that very specific input parameters can be used with reasonable values. Compared simulated values to observed data values for calibration, R2 and Nash-Stucliffe model efficiency coefficient were 0.74 and 0.65 in flow comparison, and 0.89 and 0.79 in sediment comparison. The model determined 1.0 m of Filter Length, 0.18 of Filter Slope, and 0.2 cm of Filter Media Spacing to reduce 80% of sediment by VFS. The model has not only Auto-Calibration module also DBs for specific input parameters, thus, the model is expected to be used for effective VFS scale.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.34-34
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• 2018

본 연구는 다목적 유전자 알고리즘 Non-Dominated Sorting Genetic Algorithm II (NSGA-II)를 활용하여 자동 검보정 알고리즘을 개발하고, 이를 준분포형 수문모형인 SWAT (Soil and Water Assessment Tool) 모형에 적용하여 평가하고자 한다. 집중형 모형과 달리, 분포형 모형은 유역 내 다양한 물리적 변수와 공간 이질성(spatial heterogeneity)을 표현하기 위한 많은 매개변수를 포함하고 있고, 최근에는 기후 변화와 장기 가뭄과 같은 이상 기후에 따른 물 부족, 수질 오염 및 녹조 현상 등을 고려하기 위해 매개변수의 시간적인 변동성을 고려하기 위한 연구도 수행되고 있다. 이에 따라 본 연구에서 개발한 다목적 알고리즘은 다양한 매개변수의 시공간적 특성을 고려할 수 있도록 작성되었으며, Python으로 개발하여 타 모형으로의 확장성 및 범용성을 고려하였다. SWAT 모형의 유출 해석은 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error), 모형 효율성 계수(Nash-Sutcliffe efficiency, NSE) 및 IOA(Index of agreement) 등을 활용해 기존 연구 결과와 비교분석할 수 있도록 하였으며, 사용자의 선택에 따라 다른 목적함수 또한 활용할 수 있도록 하였다. NSGA-II를 활용한 SWAT 모형의 유출 해석은 다목적 함수를 고려함에 따라 실측값과 높은 상관성을 보여줄 것으로 판단되며, 이상 기후 기간 설정에 따른 유동적인 매개변수 변화를 적용할 수 있을 것으로 기대된다.