• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.931-939
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• 2011

In practice, thresholds are determined by the two subjective assessment methods in a generalized pareto distribution of mean extreme function(MEF-graph) or Hill-graph. To remedy the problem of subjectiveness of these methods, we propose an alternative method to determine the threshold based on the robust statistics. We compared the MEF-graph, Hill-graph and our method through VaRs on the Korean stock market data from January 5, 1987 to August 3, 2009. As a result, the VaR based on the proposed method is not much different from the existing methods, and the standard deviation of VaR for our method was the smallest. The results show that our method can be a promising alternative to determine thresholds of the generalized pareto distributions.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.677-685
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• 2007

The objective of this study is to evaluate the applicability of multi-objective genetic algorithm(MOGA) in order to calibrate the parameters of conceptual rainfall-runoff model, Tank model. NSGA-II, one of the most imitating MOGA implementations, is combined with Tank model and four multi-objective functions such as to minimize volume error, root mean square error (RMSE), high flow RMSE, and low flow RMSE are used. When NSGA-II is employed with more than three multi-objective functions, a number of Pareto-optimal solutions usually becomes too large. Therefore, selecting several preferred Pareto-optimal solutions is essential for stakeholder, and preference-ordering approach is used in this study for the sake of getting the best preferred Pareto-optimal solutions. Sensitivity analysis is performed to examine the effect of initial genetic parameters, which are generation number and Population size, to the performance of NSGA-II for searching the proper paramters for Tank model, and the result suggests that the generation number is 900 and the population size is 1000 for this study.

• Bulletin of the Society of Naval Architects of Korea
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• v.31 no.1
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• pp.34-38
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• 1994

본 연구에서는 Genetic Algorithm을 사용하여 상기의 문제를 해결하고자 한다. 특히 다목적 함수 최적화에는 한 번의 최적화 계산으로 Pareto최적해 집합이 동시에 구해지는 새로운 방법인 MOGA(Multicriteria Optimization by Genetic Algorithm)을 개발하였다. 먼저 Genetic Alorithm의 기본 특성에 대해 살펴보고, 다양한 종류의 문제를 통해 Genetic Algorithm의 유용 성을 검토하였다.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.73-80
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• 2010

The optimal design of water distribution system have started with the least cost design of single objective function using fixed hydraulic variables, eg. fixed water demand and pipe roughness. However, more adequate design is accomplished with considering uncertainties laid on water distribution system such as uncertain future water demands, resulting in successful estimation of real network's behaviors. So, many researchers have suggested a variety of approaches to consider uncertainties in water distribution system using uncertainties quantification methods and the optimal design of multi-objective function is also studied. This paper suggests the new approach of a multi-objective optimization seeking the minimum cost and maximum robustness of the network based on two uncertain variables, nodal demands and pipe roughness uncertainties. Total design procedure consists of two folds: least cost design and final optimal design under uncertainties. The uncertainties of demands and roughness are considered with Latin Hypercube sampling technique with beta probability density functions and multi-objective genetic algorithms (MOGA) is used for the optimization process. The suggested approach is tested in a case study of real network named the New York Tunnels and the applicability of new approach is checked. As the computation time passes, we can check that initial populations, one solution of solutions of multi-objective genetic algorithm, spread to lower right section on the solution space and yield Pareto Optimum solutions building Pareto Front.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.21-29
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• 2015

This paper proposes a novel two-tier optimization approach for decision making in many-objective problems. Because the Pareto-optimal solution ratio increases exponentially with an increasing number of objectives, simply finding the Pareto-optimal solutions is not sufficient for decision making in many-objective problems. In other words, it is necessary to discriminate the more preferable solutions from the other solutions. In the proposed approach, user preference-oriented as well as diverse Pareto-optimal solutions can be obtained as candidate solutions by introducing an additional tier of optimization. The second tier of optimization employs the corresponding secondary objectives, global evaluation and crowding distance, which were proposed in previous works, to represent the users preference to a solution and the crowdedness around a solution, respectively. To demonstrate the effectiveness of the proposed approach, decision making for some benchmark functions is conducted, and the outcomes with and without the proposed approach are compared. The experimental results demonstrate that the decisions are successfully made with consideration of the users preference through the proposed approach.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.2
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• pp.56-64
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• 1996

In this study, a review is made of the previous work(Ref. 1 and 5) for the development of the limit design method of the flat rectangular grillages under the lateral pressure. And the effect of the in-plane loads on the collapse theory is considered. The main part of the work is devoted in developing the standard design method of grillages under the criteria of minimum weight and minimum cost. In the final part, it was shown that Pareto solution methods can be easily applied to structural optimization with the multiple objectives, and the designer can have an appropriate choice from those Pareto optimal solutions.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1219-1224
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• 2004

In this study the optimization of plate-fin type heat sink with vortex generator for thermal stability is conducted numerically. To acquire the optimal design variables, the CFD and mathematical optimization are integrated. The flow and thermal fields are predicted using the finite volume method. The optimization is carried out by means of the sequential quadratic programming (SQP) method. The results show that when the temperature rise is less than 40 K, the optimal design variables are as follows; $B_1=2.584mm$, $B_2=1.741mm$, and t = 7.914 mm. Comparing with the initial design, the temperature rise is reduced by 4.2 K, while the pressure drop is increased by 9.43 Pa. The Pareto optimal solutions are also presented between the pressure drop and the temperature rise.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.104-107
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• 2007

다목적 함수의 최적화 문제(Multiobjective optimization problems)의 경우에는 하나의 최적해가 존재하는 것이 아니라 '파레토 최적해 집합(Pareto optimal set)'이라고 알려진 해들의 집합이 존재한다. 이러한 이상적 파레토 최적해 집합과 가까운 최적해를 찾기 위한 다양한 해탐색 능력은 진화 알고리즘의 성능을 결정한다. 본 논문에서는 게임 모텔에 기반한 공진화 알고리즘(GCEA:Game model based Co-Evolutionary Algorithm)에서 해집단의 다양성을 유지하여, 다양한 비지배적 파레토 대안해(non-dominated alternatives)들을 찾기 위한 방법을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.314-322
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• 2007

This paper proposes a new optimization algorithm named by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) which determines the best configuration for CR(Cognitive Radio) communication systems. Conventionally, in order to select the proper radio configuration, genetic algorithm has been introduced so as to alleviate computational burden along the execution of the cognition cycle proposed by Mitola. This paper proposes a novel optimization algorithm designated as GBNSGA for cognitive engine which can be described as a hybrid algorithm combining well-known Pareto-based NSGA(Non-dominated Sorting Genetic Algorithm) as well as GP(Goal Programming). By conducting computer simulations, it will be verified that the proposed method not only satisfies the user's service requirements in the form of goals. It reveals the fast optimization capability and more various solutions rather than conventional NSGA or weighted-sum approach.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.2
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• pp.9-22
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• 2008

This paper presents an integrated optimal design technique of a hybrid structure-damper system for improving the seismic performance of the structure. The proposed technique corresponds to the optimal distribution of the stiffness and dampers. The multi-objective optimization technique is introduced to deal with the optimal design problem of the hybrid system, which is reformulated into the multi-objective optimization problem with a constraint of target reliability in an efficient manner. An illustrative example shows that the proposed technique can provide a set of Pareto optimal solutions embracing the solutions obtained by the conventional sequential design method and single-objective optimization method based on weighted summation scheme. Based on the stiffness and damping capacities, three representative designs are selected among the Pareto optimal solutions and their seismic performances are investigated through the parametric studies on the dynamic characteristics of the seismic events. The comparative results demonstrate that the proposed approach can be efficiently applied to the optimal design problem for improving the seismic performance of the structure.