• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.3
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• pp.431-437
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• 2010

It's strongly needed to minimize the logistics response time for supporting military operations in wartime. In this paper, we suggest the ILP formulation for minimizing logistics response time in wartime. Main structure of this formulation is based on the traveling purchaser problem(TPP) which is a generalized form of the well-known traveling salesman problem(TSP). In the case of general TPP, objective function is to minimize the sum of traveling cost and purchase cost. But, in this study, objective function is to minimize traveling cost only. That's why it's more important to minimize traveling cost(time or distance) than purchase cost in wartime. We find out optimal solution of this problem by using ILOG OPL STUDIO(CPLEX v.11.1) and do the sensitive analysis about computing time according to number of operated vehicles.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.939-944
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• 2005

In this paper, a sound quality index for the evaluation of the vehicle intake noise was developed through a correlation analysis of the objective measurement and the subjective evaluation. First, intake orifice noise was measured at the wide-open throttle sweep condition. And then, the acoustic transfer function between intake orifice noise and interior noise was measured. Simultaneously, subjective evaluation was carried out with a 10-scale score by 8 special engineers. The correlation analysis between the psychoacoustic parameters derived from the measurement and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for intake noise was obtained from the multiple factor regression analysis method. Finally, the effectiveness of the proposed index was validated.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.9 s.90
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• pp.884-890
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• 2004

In this paper, an index for the evaluation of vehicle intake booming noise is developed through a correlation analysis of objective measurement data and subjective evaluation data. First, intake orifice noise is measured at the wide-open test condition. And then, acoustic transfer function between intake orifice noise and interior noise at the steady state condition is estimated. Simultaneously, subjective evaluation was carried out with a ten-scale score by 8 engineers. Next, the correlation analysis between the psycho-acoustic parameters derived from the measured data and the subjective evaluation is performed. The most critical factor was determined and the corresponding index for the intake booming noise is obtained from the multiple factor regression method. At last, the effectiveness of the proposed index is validated.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.704-710
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• 2018

For the optimal design of electromagnetic device involving uncertainties in design variables, this paper proposes a new reliability-based optimal design algorithm for multiple constraints problems. Through optimizing the nominal objective function and maximizing the minimum reliability, a set of global optimal reliable solutions representing different reliability levels are obtained by the multi-objective particle swarm optimization algorithm. Applying the sensitivity-assisted Monte Carlo simulation method, the numerical efficiency of optimization procedure is guaranteed. The proposed reliability-based algorithm supplying multi-reliable solutions is investigated through applications to analytic examples and the optimal design of two electromagnetic problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.1-9
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• 2010

Quality design methodologies have received constituent attention from a number of researchers and practitioners for more than twenty years. Specially, the quality design for drug products must be carefully considered because of the hazards involved in the pharmaceutical industry. Conventional pharmaceutical formulation design problems with mixture experiments have been typically studied under the assumption of an unconstrained experimental region with a single quality characteristic. However, real-world pharmaceutical industrial situations have many physical limitations. We are often faced with multiple quality characteristics with constrained experimental regions. ln order to address these issues, the main objective of this paper is to propose a robust desirability function (RDF) model using a desirability function (DF) and mean square error (MSE) to simultaneously consider a number of multiple quality characteristics. This paper then present L-pseudocomponents and U-pseudocomponents to handle physical constraints. Finally, a numerical example shows that the proposed RDF can efficiently be applied to a pharmaceutical process design.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.251-254
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• 2000

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

• The Journal of Engineering Geology
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• v.25 no.1
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• pp.67-81
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• 2015

A FORTRAN program was developed to determine the optimal locations of multiple recharge wells in an aquifer with different arrangements of pumping wells. The simulated annealing algorithm was used to find optimal locations of two recharge wells which satisfied three objective functions. The model results show that locating two injection wells inside the cluster of pumping wells is efficient if the recovery rate only was taken into account. In contrast, placing injection wells to the side of the cluster is desirable if the simulation considers aggregate objective function. Therefore, installing an injection well on each side of the cluster seems to yield the maximum recovery rates for the existing pumping wells, and it yields similar increases in pumping rate for all wells in the cluster. The locations of recharge wells can be arranged in numerous configurations, because there are multiple near-optimal local minima or maxima. These results indicate that the simulated annealing can yield effective evaluations of the optimal locations of multiple recharge wells. In addition, the suggested aggregate objective function can be utilized as an appropriate multi-objective optimization.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2150-2158
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• 2002

A recent research and development has the requirement for the optimization to shorten design time of modified or new product model and to obtain more precise engineering solution. General optimization problem must consider many conflicted objective functions simultaneously. Multi-objective optimization treats the multiple objective functions and constraints with design change. But, real engineering problem doesn't describe accurate constraint and objective function owing to the limit of representation. Therefore this study applies variance analysis on the basis of structure analysis and DOE to the vertical roller mill fur portland cement and proposed statistical design model to evaluate the effect of structural modification with design change by performing practical multi-objective optimization considering mass, stress and deflection.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.