• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.41-50
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• 1997

In this paper, we presents the method for finding the compensatory solution for fuzzy multiobjective nonlinear programming problem with fuzzy parameters involved in the problem-formulation process and fuzzy equal goals of the decision maker for each of the objective functions. The fuzzy parameters in the objective functions and the constraints characterized by fuzzy numbers. The proposed method can be applied to case with multiobjective problems and guarantee an efficient solution. An illustrative numerical example is presented.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.713-724
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• 2013

In terms of waste load allocation, inequality of waste load discharge must be considered as well as economic aspects such as minimization of waste load abatement. The inequality of waste load discharge between areas was calculated with Gini coefficient and was included as one of the objective functions of the multi-objective waste load allocation. In the past, multi-objective functions were usually weighted and then transformed into a single objective optimization problem. Recently, however, due to the difficulties of applying weighting factors, multi-objective genetic algorithms (GA) that require only one execution for optimization is being developed. This study analyzes multi-objective waste load allocation using NSGA-II-aJG that applies Pareto-dominance theory and it's adaptation of jumping gene. A sensitivity analysis was conducted for the parameters that have significant influence on the solution of multi-objective GA such as population size, crossover probability, mutation probability, length of chromosome, jumping gene probability. Among the five aforementioned parameters, mutation probability turned out to be the most sensitive parameter towards the objective function of minimization of waste load abatement. Spacing and maximum spread are indexes that show the distribution and range of optimum solution, and these two values were the optimum or near optimal values for the selected parameter values to minimize waste load abatement.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.65.1-65.1
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• 2010

Thermal performance tests of solar thermal collectors include determination of coefficient parameters in an efficiency equation. The parameters can be estimated using regression method to minimize an objective function as sum of differences between measured efficiency data and regressed efficiency equation. However, this conventional approach doesn't consider measurement uncertainties. In this presentation, a method to determine regression parameters in the efficiency equation and uncertainties of the parameters is described with mainly mathematical expressions based on literature reviews. In the method, parameters in the equation for collector efficiency can be determined using regression analysis with a weighting factor in the objective function. The weighting factor can be uncertainties of the differences between measured and fitted efficiencies. To evaluate the approach, performance estimation of a solar collector using the efficiency equation with uncertainties is compared to the result using the conventional efficiency equation by a simulated way for a case in one of previous studies.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.1898-1909
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• 1993

In this paper, a convenient scheme for solving multi-objective optimization problems including fuzzy information in both objective functions and constraints is presented. At first, a multi-objective problem is converted into single objective problem based on the norm method, and a merbership function is constructed by selecting its type and providing the parameters defined by the norm method. Finally, this fuzzy programming problem is converted into an ordinary optimization problem which can be solved by usual nonlinear programming techniques. With this scheme, a designer can conveniently obtain pareto optimal solutions of a fuzzy system only by providing some parameters corresponding to the importance of the objectiv functions. Proposed scheme is simple and efficient in treating multi-objective fuzzy systems compared with and method by with membership function value is provided interactively. To show the validity of the scheme, a simple 3-bar truss example and optimal cutting problem are solved, and the results show that the scheme is very useful and easy to treat multi-objective fuzzy systems.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.48-53
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• 2000

To analyze a room reverberation, many objective parameters have been suggested as measures of subjective perception in concert hall acoustics. However, it is difficult to understand the relationship among the individual parameters and to have a whole image of them. In this paper five primary objective parameters were selected and a reverberation model based on them was established by the reverberation decay curve. The proposed model was interpreted geometrically in terms of subjective characteristics. And finally we discuss the usefulness and the limitation of the model when it is applied to the analysis and.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.938-943
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• 2013

In this paper, we propose a transmission parameter optimization scheme based on genetic algorithm for dynamic spectrum access systems. Specifically, we represent a multiple objective fitness function as a weighted sum of single objective fitness functions to optimize transmission parameters, and then, obtain optimized transmission parameters based on genetic algorithm for given transmission scenarios. From numerical results, we confirm that the transmission parameters are well optimized by using the proposed optimization scheme.

• Journal of the Korea Safety Management & Science
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• v.4 no.1
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• pp.131-139
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• 2002

Since introducing the "Theory of Constraints" by Goldratt, its effect was verified by lots of scholars, men of enterprise. These days it is also introducing and studying in this country with good results. The objective of this study is to show how to determine the constraint resources on DBR scheduling. Actually, previous studies based on the line which just think a load/capacity rate on doing scheduling. This study will show a scheduling method which reflects multi-parameters. It could be a standard to reflect real manufacturing surroundings. On calculating a priority of each resources, we classified factors with subjective and objective factors. And we propose a decision model to incorporate values assigned by a group of experts on different factors to select a critical resource. On deploying this model, SN ratio of Taguchi method for each of subjective and objective factors will be used. And we propose a procedure which is organized with 7 steps. To understand the logic, a numerical manufacturing simulation will be presented. This method is a incorporating decision model on determining the constraint on multi parameters with experts.h experts.

• Transactions of Materials Processing
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• v.30 no.1
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• pp.27-34
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• 2021

In this study, response surface method (RSM) was used in modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goals of optimization were the maximum forming angle, minimum thickness reduction, and minimum surface roughness, with varying values in response to changes in production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model for modeling the variations in the forming angle, thickness reduction, and surface roughness in response to variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process based on experimental design. The results showed that RSM can be effectively used to control the forming angle, thickness reduction, and surface roughness.

• Journal of Power System Engineering
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• v.3 no.4
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• pp.63-68
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• 1999

The determination of the optimal machining parameters in metal cutting, such as cutting speed, feed rate, and depth of cut, is an important aspect in an economic manufacturing process. The main objective in general is either to minimize the production cost or to maximize the production rate. Also there are constraints on all the machining operations which put restrictions on the choice of the machining parameters. In this paper as an objective function the production cost is considered with two constraints, surface finish and cutting power. Genetic Algorithm is applied to determine the optimum machining parameters, and the effectiveness of the applied algorithm is demonstrated by means of an example, turning operation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.7
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• pp.814-819
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• 2016

The Stockbridge damper is used to control the aeolian vibration of a overhead transmission line due to the natural wind under a low velocity, between 1 m/s to 7 m/s. The damper model can be simply derived with several design parameters and the location of eigenvalues of design parameters are important to determine the efficiency of energy dissipation by excitation itself with two counterweights. First, the importance of resonance frequencies of Stockbridge damper was reviewed through the analysis of frequency response function of damper system. Then, the best selection of design parameters was investigated with the introduction of objected function that minimize the distance between the calculated eigenvalues and target frequency points. The best choice of design parameters was reviewed using the simulated results from the objective function and the effectiveness of selected design case was discussed at the point view of practical implementation.