• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.27-39
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• 2004

In the first part of this study, five homogeneous regions in view of topographical and geographically homogeneous aspects except Jeju and Ulreung islands in Korea were accomplished by K-means clustering method. A total of 57 rain gauges were used for the regional frequency analysis with minimum rainfall series for the consecutive durations. Generalized Extreme Value distribution was confirmed as an optimal one among applied distributions. Drought rainfalls following the return periods were estimated by at-site and regional frequency analysis using L-moments method. It was confirmed that the design drought rainfalls estimated by the regional frequency analysis were shown to be more appropriate than those by the at-site frequency analysis. In the second part of this study, LH-moment ratio diagram and the Kolmogorov-Smirnov test on the Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions were accomplished to get optimal probability distribution. Design drought rainfalls were estimated by both at-site and regional frequency analysis using LH-moments and GEV distribution, which was confirmed as an optimal one among applied distributions. Design rainfalls were estimated by at-site and regional frequency analysis using LH-moments, the observed and simulated data resulted from Monte Carlotechniques. Design drought rainfalls derived by regional frequency analysis using L1, L2, L3 and L4-moments (LH-moments) method have shown higher reliability than those of at-site frequency analysis in view of RRMSE (Relative Root-Mean-Square Error), RBIAS (Relative Bias) and RR (Relative Reduction) for the estimated design drought rainfalls. Relative efficiency were calculated for the judgment of relative merits and demerits for the design drought rainfalls derived by regional frequency analysis using L-moments and L1, L2, L3 and L4-moments applied in the first report and second report of this study, respectively. Consequently, design drought rainfalls derived by regional frequency analysis using L-moments were shown as more reliable than those using LH-moments. Finally, design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were derived by regional frequency analysis using L-moments, which was confirmed as a more reliable method through this study. Maps for the design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were accomplished by the method of inverse distance weight and Arc-View, which is one of GIS techniques.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.95-108
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• 2006

Because of rapid expansion of third party logistics, fierce competition in the transportation industry, and the diversification and globalization of transportation channels, an effective transportation planning by means of multimodal transport is badly needed. Accordingly, this study aims to suggest an optimal transport algorithm for the multimodal transport in the international logistics. Cargoes and stopovers can be changed numerously according to the change of transportation modes, thus being a NP-hard problem. As a solution for this problem, first of all, we have applied a pruning algorithm to simplify it, suggesting a heuristic algorithm for constrained shortest path problem to find out a feasible area with an effective time range and effective cost range, which has been applied to the Label Setting Algorithm, consequently leading to multiple Pareto optimal solutions. Also, in order to test the efficiency of the algorithm for constrained shortest path problem, this paper has applied it to the actual transportation path from Busan port of Korea to Rotterdam port of Netherlands.

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.189-203
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• 1992

Any money model should address the most important phenomenon of a monetary economy, which is the phenomenon of the rate of return dominance. Even if the holding returns on financial or nonfinancial assets are higher than the rate of return on fiat money holding, which is typically zero, people still hold and use money. In a period of accelerating inflation, number of dominating assets increases continuously, yet people continue to hold and use money. Wallace's (1980) overlapping generations model cannot address the rate of return dominance phenomenon. His model does not capture the mediun of exchange role of fiat money. In this paper, an overlapping types model of fiat money is constructed, in which different types of consumers have different preferences on different types of goods, are endowed with different types of goods, are located at seperated regions, and live for only two periods. In this model, people hold and use money despite the dominating assets, even if inflation accelates. Money in this case serves as a pure medium of exchange, whereas in Wallace's model, money serves as a pure store of value, and money disappears if a dominating asset exists. An interesting feature of the overlapping types model presented in this paper is that money does not provide a cheap approximation to an idealized and efficient real allocation. A monetary economy is always superior to a nonmonetary economy, because money helps overcome the incompleteness of the overlapping types friction. In a monetary economy, however, a pareto optimal allocation cannot always be achieved, because money cannot always overcome the overlapping types friction itself. Therefore, with the criterion of optimality of real allocations, the monetary economy is more optimal than a nonmonetary economy but less optimal than a complete Arrow-Debreu economy. This feature has important implications on macro modelling. Because of the difficulty in introducing money into a macro model in an essential and endogenous manner as in the overlapping types model of this paper, a macro model typically ignores money and studies real allocations without the money factor. The possible inefficiencies of a monetary economy, relative to a complete real Arrow-Debreu economy, may indicate differences in real allocations between the two models.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1299-1305
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• 2017

In this paper, we consider a beamforming game between the transmitters in a two-user multiple-input single-output interference channel using limited feedback and investigate how each transmitter is able to find a modified strategy from the quantized channel state information (CSI). In the beamforming game, each of the transmitters (i.e., a player) tries to maximize the achievable rate (i.e., a payoff function) via a proper beamforming strategy. In our case, each transmitter's beamforming strategy is represented by a linear combining factor between the maximum ratio transmission (MRT) and the zero forcing (ZF) beamforming vectors, which is the Pareto optimal achieving strategy. With the quantized CSI, the transmitters' strategies may not be valid because of the quantization errors. We propose a modified solution, which takes into account the effects of the quantization errors.

• Environmental and Resource Economics Review
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• v.12 no.1
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• pp.75-90
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• 2003

In this paper we have shown that a Pigouvian tax is an adequate resolution of congestion externality to attain Pareto optimality using utility maximization. For this objective, taking an open access freeway as an example, we not only derived both marginal private benefit and marginal social benefit, but also assessed the divergence between marginal private benefit and marginal social benefit. As a result, we identified that the amount of a Pigouvian tax should be the same amount as the external time cost, which is the value of the marginal time cost to Individual a incurred by Individual b through freeway congestion. This Pigouvian tax coincides with the profit or wealth maximizing toll suggested by literature on the basis of profit maximization. In addition, because an open access freeway is accounted as common property resource, we proved that average social congestion cost is essentially equal to marginal private congestion cost in our model. Finally, we showed that the optimal value of trip derived in our model is the same as that generated on profit maximization approach.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.77-86
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• 2000

The shortest path problem is one of the mathematical Programming models that can be conveniently solved through the use of networks. The common shortest Path Problem is to minimize a single objective function such as distance, time or cost between two specified nodes in a transportation network. The sing1e objective model is not sufficient to reflect any Practical Problem with multiple conflicting objectives in the real world applications. In this paper, we consider the shortest Path Problem under multiple objective environment. Wile the shortest path problem with single objective is solvable in Polynomial time, the shortest Path Problem with multiple objectives is NP-complete. A genetic a1gorithm approach is developed to deal with this Problem. The results of the experimental investigation of the effectiveness of the algorithm are also Presented.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.893-904
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• 2013

In this paper, a Kriging metamodel-based multi-objective optimization strategy in conjunction with an NSGA-II(non-dominated sorted genetic algorithm-II) has been employed to optimize the valve-plate shape of the axial piston pump utilizing 3D CFD simulations. The optimization process for minimum pressure ripple and maximum pump efficiency is composed of two steps; (1) CFD simulation of the piston pump operation with various combination of six parameters selected based on the optimization principle, and (2) applying a multi-objective optimization approach based on the NSGA-II using the CFD data set to evaluate the Pareto front. Our exploration shows that we can choose an optimal trade-off solution combination to reach a target efficiency of the axial piston pump with minimum pressure ripple.

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.93-102
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• 2010

In this study, a smart sky-bridge composed of MR damper and FPS has been proposed and vibration control performance of a smart sky-bridge for the connected buildings was investigated. To this end, 10-story and 20-story building structures connected by a smart sky-bridge were selected as example structures and El Centro and Kobe earthquakes, which have near and far fault ground motion characteristics respectively, were used for time history analyses. In order to effectively control the smart sky-bridge, fuzzy logic controller was developed and multi-objective genetic algorithm was used to optimize fuzzy logic controllers. Based on optimization results, it has been seen that there is a trade-off between seismic responses of 10-story and 20-story buildings and a suite of Pareto optimal solutions of fuzzy logic controllers for seismic response control can be obtained by multi-objective genetic algorithm. It is shown from numerical study that seismic responses of adjacent buildings can be efficiently controlled by using a smart sky-bridge.