• IE interfaces
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• v.24 no.3
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• pp.220-230
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• 2011

The multi-reservoir operation problem for efficient utilization of water resources involves conflicting objectives, and the problem can be solved by varying weight coefficient on objective functions. Accordingly, decision makers need to choose appropriate weight coefficients balancing the trade-offs among multiple objectives. Although the appropriateness of the weight coefficients may depend on the total amount of water inflow, reservoir operating policy may not be changed to a certain degree for different hydrological conditions on inflow. Therefore, we propose to use fuzzy Data Envelopment Analysis (DEA) to rank the weight coefficients in consideration of the inflow variation. In this approach, we generate a set of Paretooptimal solutions by applying different weight coefficients on Coordinated Multi-reservoir Operating Model. Then, we rank the Pareto-optimal solutions or the corresponding weight coefficients by using Fuzzy DEA model. With the proposed approach, we can suggest the best weight coefficients that can produce the appropriate Pareto-optimal solution considering the uncertainty of inflow, whereas the general DEA model cannot pinpoint the best weight coefficients.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.323-334
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• 2023

The submerged floating tunnel (SFT) infrastructure has been regarded as an emerging technology that efficiently and safely connects land and islands. The SFT route problem is an essential part of the SFT planning and design phase, with significant impacts on the surrounding environment. This study aims to develop an optimization model considering transportation and structure factors. The SFT routing problem was optimized based on two objective functions, i.e., minimizing total travel time and cumulative strains, using NSGA-II. The proposed model was applied to the section from Mokpo to Jeju Island using road network and wave observation data. As a result of the proposed model, a Pareto optimum curve was obtained, showing a negative correlation between the total travel time and cumulative strain. Based on the inflection points on the Pareto optimum curve, four optimal SFT routes were selected and compared to identify the pros and cons. The travel time savings of the four selected alternatives were estimated to range from 9.9% to 10.5% compared to the non-implemented scenario. In terms of demand, there was a substantial shift in the number of travel and freight trips from airways to railways and roadways. Cumulative strain, calculated based on SFT distance, support structure, and wave energy, was found to be low when the route passed through small islands. The proposed model helps decision-making in the planning and design phases of SFT projects, ultimately contributing to the progress of a safe, efficient, and sustainable SFT infrastructure.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1011-1027
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• 2010

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.56-66
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• 1998

This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.

• 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 Communications and Networks
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• v.15 no.5
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• pp.486-495
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• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.124-145
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• 2014

Market failure occurs when Pareto efficiency is not achieved through market mechanism. In order to solve this problem, government intervene market; paying great attention to the optimum state of resource allocation. However, as the size of government investment in R&D goes up, many professionals emphasize the importance in efficient management system. This work is the result of exploratory study to look into life-cycle management of governmental R&D program. Literature reviews and empirical research on governmental R&D programs elicit improvements for effective life-cycle management of governmental R&D program as follows: consistent discrimination between capital expenditure and recurring expenditure, dual management system by spending properties, implementing total cost management system in capital expenditure, and discrimination between preliminary feasibility study with confirming total program cost in recurring expenditure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.441-450
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• 2006

Recently, with the exponential growth of the number of Internet users, IP traffic which occupies more than 90 percent of the entire Internet traffic affects significantly to the performance of networks. Therefore, the design of the self-similar traffic generator reflected the feature of IP traffic is very important to design the networks efficiently and evaluate the performance of it correctly. In this paper, we design the self-similar traffic generator using OPNET. In order to implement the self-similar characteristics, ON-OFF sources with Pateto distribution are employed and aggregated. The designed self-similarity traffic generator is evaluated and verified with R/S plot, variance time(VT) plot under the various offered loads and the number of sources. It is expected that the designed self-similar traffic generator can be put to practical use when wire or wireless networks is designed and verified as well as it can be useful to decide the specific parameter value for Internet traffic modeling.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.