• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1512-1518
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• 2004

Rescaled Simulated Annealing (RSA) has been adapted to solve combinatorial optimization problems in which the available computational resources are limited. Simulated Annealing (SA) is one of the most popular combinatorial optimization algorithms because of its convenience of use and because of the good asymptotic results of convergence to optimal solutions. However, SA is too slow to converge in many problems. RSA was introduced by extending the Metropolis procedure in SA. The extension rescales the state's energy candidate for a transition before applying the Metropolis criterion. The rescaling process accelerates convergence to the optimal solutions by reducing transitions from high energy local minima. In this paper, structural optimization examples using RSA are provided. Truss structures of which design variables are discrete or continuous are optimized with stress and displacement constraints. The optimization results by RSA are compared with the results from classical SA. The comparison shows that the numbers of optimization iterations can be effectively reduced using RSA.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1028-1033
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• 2004

The heat and flow characteristics in a single-phase parallel-flow heat exchanger was examined numerically to obtain its optimal shape. A response surface method was introduced to predict its performance approximately with respect to design parameters over design domain. Design parameters are inflow and outflow angle of the working fluid and horizontal and vertical location of inlet and outlet. The evaluation of the relative priority of the design parameters was performed to choose three important parameters in order to use a response surface method. A JF factor was used as an evaluation characteristic value to consider the heat transfer and the pressure drop simultaneously. The JF factor of the optimum model, compared to that of the base model, was increased by about 5.3%.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.04a
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• pp.125-129
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• 1996

This paper deals with the problem of placement/sizing of distributed piezo actuators to achieve the control objective of vibration suppression. Using the mean square response as a performance index in optimization, we obtain optimal placement and sizing of the actuator. The use of genetic algorithms as a technique for solving optimization problems of placement and sizing is explored. Genetic algorithms are also used for the control strategy. The analysis of the system and response moment equations are carried out by using the Fokker-Planck equation. This paper presents the design and analysis of an active controller and optimal placement/sizing of distributed piezo actuators based on genetic algorithms for a flexible structure under random disturbance, shows numerical example and the result.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.153-159
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• 2004

A control-structure combined optimal design problem is discussed taking a 3-D truss structure as a design object. We use descriptor forms for a controlled object and a generalized plant because the structural parameters appear naturally in these forms. We consider not only minimum weight design problem for structure system, but also suppression problem of the effect of disturbances for control system as the purpose of the design. By minimizing the linear sum of the normalized structural objective function and control objective function, it is possible to make optimal design by which the balance of the structural weight and the control performance is taken.

• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.3
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• pp.174-179
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• 2007

In this paper, we present a optimal module selection using genetic algorithm under the power, area, delay constraint. The proposed algorithm use the way of optimal module selection it will be able to minimize power consumption. In the comparison and experimental results, The proposed application algorithm reduce maximum power saving up to 26.9% comparing to previous non application algorithm, and reduce minimum power saving up to 9.0%. It also show the average power saving up to 15.525% and proved the power saving efficiency.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.272-287
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• 2012

The optimal use of sonar systems for detection is a practical problem in a given ocean environment. In order to quantify the mission achievability in general, measure of effectiveness(MOE) is defined for specific missions. In this paper, using the specific MOE for detection, which is represented as cumulative detection probability(CDP), an integrated software package named as Optimal Acoustic Search Path Planning(OASPP) is developed. For a given ocean environment and sonar systems, the discrete observations for detection probability(PD) are used to calculate CDP incorporating sonar and environmental parameters. Also, counter-detection probability is considered for vulnerability analysis for a given scenario. Through modeling and simulation for a simple case for which an intuitive solution is known, the developed code is verified.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.70-89
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• 1996

This paper discusses an optimal burn -in procedure to minimize total costs based on the assumption that some of the components are weak for stress and deteriorate faster than the main components. The procedure will define the costs of burn-in errors. An ideal burn-in consists of process in which all weak (substandard) components and no main (standard) components fail. In practice, the burn-in errors could occur for some reasons. For example, it is impossible to eliminate all weak components through burn-in, due to a nonzero proportion of defectives of the components. Probability model and cost function model are formulated to find the optimal burn-in time that minimizes the expected total cost. Several examples are included to show how to use the results.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2262-2267
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• 2018

In electric machine design, there is a large computation cost for finite element analyses (FEA) when analyzing nonlinear characteristics in the machine Therefore, for the optimal design of an electric machine, designers commonly use an optimization algorithm capable of excellent convergence performance. However, robustness consideration, as this factor can guarantee machine performances capabilities within design uncertainties such as the manufacturing tolerance or external perturbations, is essential during the machine design process. Moreover, additional FEA is required to search robust optimum. To address this issue, this paper proposes a computationally efficient robust optimization algorithm. To reduce the computational burden of the FEA, the proposed algorithm employs a useful technique which termed static analysis assisted technique (SAAT). The proposed method is verified via the effective robust optimal design of electric machine to reduce cogging torque at a reasonable computational cost.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1237-1245
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• 2019

Most of the blind are low vision blinds due to injury or disease. As their vision decreases, they are experiencing inconvenience in their normal life and forgetting their memories with their family. The purpose of this study is to use Lithophane printing technology to help their normal life and to remember their family. Also, the manufactured 3D plates are to study the conditions that can be optimal understood through the tactile sense of low vision blind. When the low vision blind person understood the 3D plates, they chose three parameters that affect their tactile sense. And by comparing their tactile sense, the optimal condition results were found. This paper was concluded with (1) the round form that perceived as 3D objects, (2) the thin thickness similar to Braille, and (3) the high resolution that can be expressed in detail.