• 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 Mechanical Science and Technology
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• v.20 no.3
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• pp.366-375
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• 2006

In this paper, it is intended to introduce a method to solve multi-objective optimization problems and to evaluate its performance. In order to verify the performance of this method it is applied for a vertical roller mill for Portland cement. A design process is defined with the compromise decision support problem concept and a design process consists of two steps: the design of experiments and mathematical programming. In this process, a designer decides an object that the objective function is going to pursuit and a non-linear optimization is performed composing objective constraints with practical constraints. In this method, response surfaces are used to model objectives (stress, deflection and weight) and the optimization is performed for each of the objectives while handling the remaining ones as constraints. The response surfaces are constructed using orthogonal polynomials, and orthogonal array as design of experiment, with analysis of variance for variable selection. In addition, it establishes the relative influence of the design variables in the objectives variability. The constrained optimization problems are solved using sequential quadratic programming. From the results, it is found that the method in this paper is a very effective and powerful for the multi-objective optimization of various practical design problems. It provides, moreover, a reference of design to judge the amount of excess or shortage from the final object.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.41-54
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• 2005

In this paper, we consider a multi-objective machine cell formation problem. This problem Is characterized as determining part route families and machine cells such that total sum of inter-ceil part movements and maximum machine workload imbalance are simultaneously minimized. Together with the objective function, alternative part routes and the machine sequences of part routes are considered In grouping Part route families. Due to the complexity of the problem, a two-phase heuristic algorithm is proposed. And we developed an n-stage look-ahead heuristic algorithm that generalizes the roll-out algorithm. Computational experiments were conducted to verify the performance of the algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.463-468
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• 2004

This paper was applied space harmonic method as a characteristic analysis technique for slotless PMLSM. There is advantages of active response to the change of design parameters as well as reduction of the calculation time. The method can be overcome disadvantages of finite element analysis that needs long times calculation, repetitions of pre and post-process. In this paper, 3D-space harmonic method was applied to consider the precise description of end turn coil shape and the changes of characteristic according to changes of length of z-axis direction. The thrust of optimal design was performed using genetic algorithm to enhance the thrust which is the disadvantage of slotless type PMLSM. For design parameters, width of permanent magnet, width of coil, width of coil inner and lengths of z-axis direction were selected. For objective functions. thrust per weight. thrust per volume. multi-objective function was selected.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.77-79
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• 2008

The power expansion planning is large and capital intensive capacity planning. In the past, the expansion planning was established with the proper supply reliability in order to minimize social cost. However, the planning not used cost minimizing objective function in the power markets with many market participants. This paper proposed the power expansion planning model using multi-criteria decision rule. This model used multi objective function considering not only cost minimizing but also GENCO's intension. This paper compared proposed model with WASP model in order to verify the result of proposed model.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.1-7
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• 2021

In this paper, we propose a feature selection technique for multi-label classification. Many existing feature selection techniques have selected features by calculating the relation between features and labels such as a mutual information scale. However, since the mutual information measure requires a joint probability, it is difficult to calculate the joint probability from an actual premise feature set. Therefore, it has the disadvantage that only a few features can be calculated and only local optimization is possible. Away from this regional optimization problem, we propose a feature selection technique that constructs a low-rank space in the entire given feature space and selects features with sparsity. To this end, we designed a regression-based objective function using Nuclear norm, and proposed an algorithm of gradient descent method to solve the optimization problem of this objective function. Based on the results of multi-label classification experiments on four data and three multi-label classification performance, the proposed methodology showed better performance than the existing feature selection technique. In addition, it was showed by experimental results that the performance change is insensitive even to the parameter value change of the proposed objective function.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.620-621
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• 2015

In this study, the multi-criteria decision-making model based on Quality Function Deployment Method is proposed. Multicriteria decision-making is an attempt to link QFD method with the TOPSIS. By this effort, a model that makes client's decision-making more rational and objective in design phase is suggested. The multi-criteria decisionmaking model confirming to the Owner's requirements will improve the productivity of the construction industry and the satisfaction of the customer. Further study extending the range of the requirements, not only the Owner's requirement will be necessary to cover the various factors as much as possible. And then, finally as a flexible platform to achieve a sustainable quality management, web-based multi-criteria decision-making model can be utilized by the relevant stakeholders simultaneously with the feed-back and sharing the necessary informations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.163-168
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• 2005

It is one of the most important things to determinate optimized cutting conditions which satisfy productivity and cost simultaneously in production and CAPP systems. These days many researchers have figured out the optimizing way for solutions of multi-object function to find the approach methods using algorithm such as genetic algorithm or tabu search, etc., instead of mathematical methods. The main creation of objective function is proposed by empirical method but which is difficult to set it up and to analysis. In this paper, an optimization method of cutting condition is shown using the ANN and GA for the multi-objective function in high speed machining.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.428-435
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• 2013

Flexible AC Transmission System (FACTS) application study on enhancing the flexibility of AC power system has continued to make progress. A thyristor-controlled series capacitor (TCSC) is a useful FACTS device that can control the power flow by adjusting line impedances and minimize the loss of power flow and voltage drop in a transmission system by adjusting line impedances. Reduced power flow loss leads to increased loadability, low system loss, and improved stability of the power system. This study proposes the optimal location and compensation rate method for TCSCs, by considering both the power system loss and voltage drop of transmission systems. The proposed method applies a multi-objective function consisting of a minimizing function for power flow loss and voltage drop. The effectiveness of the proposed method is demonstrated using IEEE 14- and a 30-bus system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.211-220
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• 2017

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.