• Journal of the Korean Society for Railway
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• v.13 no.2
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• pp.222-228
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• 2010

In this paper, we propose a optimization approach for the Electric Locomotive Overhaul Maintenance Facility (ELOMF), which aims at the simulation optimization so as to meet the design specification. In simulation design, we consider the critical path and sensitivity analysis of the critical (dependent) factors and the design (independent) parameters for the parameter selection and reduction of the metamodel. Therefore, we construct the multi-objective non-linear programming. The objective function is normalized for the generalization of design parameter while the constraints are composed of the simulation-based regression metamodel for the critical factors and design factor's domain. Then the effective solution procedure based on the pareto optimal solution set is proposed. This approach provides a comprehensive approach for the optimization of Train Overhaul Maintenance Facility(TOMF)'s design parameters using the simulation and metamoels.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.93-102
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• 2009

A prediction of streamflow based on multi-objective function is presented to check the performance of Probability Distributed Model(PDM) in Miho stream basin, Chungcheongbuk-do, Korea. PDM is a lumped conceptual rainfall runoff model which has been widely used for flood prevention activities in UK Environmental Agency. The Monte Carlo Analysis Toolkit(MCAT) is a numerical analysis tools based on population sampling, which allows evaluation of performance, identifiability, regional sensitivity and etc. PDM is calibrated for five model parameters by using MCAT. The results show that the performance of model parameters(cmax and k(q)) indicates high identifiability and the others obtain equifinality. In addition, the multi-objective function is applied to PDM for seeking suitable model parameters. The solution of the multi-objective function consists of the Pareto solution accounting to various trade-offs between the different objective functions considering properties of hydrograph. The result indicated the performance of model and simulated hydrograph are acceptable in terms on Nash Sutcliffe Effciency*(=0.035), FSB(=0.161), and FDBH(=0.809) to calibration periods, validation periods as well.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.539-550
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• 2005

The spanning tree, which is being used the most widely in indoor wiring network, is chosen for the network topology of the optimal LAN design. To apply a spanning tree to GA, the concept of $Pr\ddot{u}fer$ numbers is used. $Pr\ddot{u}fer$ numbers can express he spanning tree in an efficient and brief way, and also can properly represent the characteristics of spanning trees. This paper uses Pareto Stratum-Niche Cubicle(PS-NC) GA by complementing the defect of the same priority allowance in non-dominated solutions of pareto genetic algorithm(PGA). By applying the PS-NC GA to the LAN design areas, the optimal LAN topology design in terms of minimizing both message delay time and connection-cost could be accomplished in a relatively short time. Numerical analysis has been done for a hypothetical data set. The results show that the proposed algorithm could provide better or good solutions for the multi-objective LAN design problem in a fairly short time.

• Journal of the Korean Society for Railway
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• v.13 no.5
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• pp.535-540
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• 2010

We present an optimization model for how to assign the freight trains to transshipment tracks and allocate the containers to the freight trains in a rail container terminal. We formulate this problem as a multi-criteria integer programming to minimize the makespan of job schedule and simultaneously to maximize the loading throughput, i.e. the number of containers to be disposed per day. We also apply our model to the instance obtained from the real-world data of the Uiwang Inner Container Depot. From the experiments, we can see an improvement of approximately 6% in makespan, which means that our model can contribute to the improvement of the disposal capacity of containers without additional expansion of facilities.

• IE interfaces
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• v.21 no.1
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• pp.75-84
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• 2008

It is a difficult task for decision makers(DMs) to choose an appropriate release plan which balances the conflicts between water storage and hydro-electric energy generation in a multi-reservoir operation problem. In this study, we proposed a DEA-based ranking procedure by which the DM can rank the potential alternatives and select the best solution among the Pareto-optimal solutions. The proposed procedure can resolve the problem of mix inefficiency that may cause errors in measuring the efficiency of alternatives. We applied the proposed procedure to the multi-reservoir operation problem for the Geum-River basin and could choose the best efficient solution from the Pareto-set which were generated by the Coordinated Multi-Reservoir Operating Model.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.474-477
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• 2009

본 연구에서는 5MW급 수평축 풍력발전 블레이드에 대한 정격풍속과 낮은 풍속 영역을 고려하여 풍속에 대한 다점 최적설계를 수행하였다. 다점 최적설계를 수행하기 위해 블레이드 해석은 Blade Element and Momentum theory를 이용 하였으며, 설계 시 적용된 기저형상은 NREL에서 제안한 5MW급 풍력터빈 블레이드이다. 최적화 과정을 통해 얻어진 최적해의 집합에 대하여 L2 Norm을 통한 파레토분석을 하였으며, 이를 통해 기저형상의 연간 에너지생산량과 설비 이용률을 보다 향상 시킬 수 있었다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.331-334
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• 2010

본 논문에서는 준능동 TMD가 설치된 고층건물의 풍응답을 효과적으로 저감시키기 위하여 다목적 유전자알고리즘(MOGA)을 이용한 퍼지관리제어기를 개발하였다. 퍼지관리제어기는 하위제어기인 그라운드훅(groundhook) 제어알고리즘과 스카이훅(skyhook) 제어알고리즘에 의해서 결정된 제어명령을 적절하게 하나로 합치는 역할을 한다. 다목적 유전자알고리즘의 최적화 과정에서 75층의 가속도 응답과 준능동 TMD의 변위응답을 목적함수로 사용하였다. 다목적 유전자알고리즘 최적화과정을 통하여 퍼지관리제어기의 파레토 최적해집합을 효과적으로 얻을 수 있었다. 다목적 유전자알고리즘에 의하여 개발된 퍼지관리제어기는 가중합방법의 제어기보다 매우 우수한 성능을 나타내었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.395-398
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• 2002

본 논문에서는 ‘다목적 함수 최적화 문제(Multi-objective Optimization Problem MOP)’를 풀기 위하여 유전자 알고리즘을 진화적 게임 이론 적용시킨 ‘내쉬 유전자 알고리즘(Nash GA)’과 본 논문에서 새로이 제안하는 공진화 알고리즘의 구조를 설명하고 이 두 알고리즘의 결과를 시뮬레이션을 통하여 비교 검토함으로써 ‘진화적 게임 이론(Evolutionary Game Theory : EGT)’의 두 가지 아이디어 -‘내쉬의 균형(Equilibrium)’과 ‘진화적 안정전략(Evolutionary Stable Strategy . ESS)’-에 기반한 최적화 알고리즘들이 다목적 함수 문제의 최적해를 탐색할 수 있음을 확인한다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.43-52
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• 2007

As the number of public Web Services increases, there will be many services with the same functionality. These services. however, will vary in their QoS properties, such as price, response time and availability, and it is very important to choose a best service while satisfying given QoS constraints. This paper brings parallel branching and response time constraint of business processes into focus and investigates several service selection plans based on multidimensional multiple choice Knapsack model. Specifically. proposed in the paper are a plan with response time constraints for each execution flow, a plan with a single constraint over the whole service types and a plan with a constraint on a particular execution path of a composite Web Services. Experiments are conducted to observe the performance of each plan with varying the number of services, the number of branches and the values of response time constraint. Experimental results show that reducing the number of candidate services using Pareto Dominance is very effective and the plan with a constraint over the whole service types is efficient in time and solution quality for small to medium size problems.

• 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.