• Journal of Korea Society of Industrial Information Systems
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• v.10 no.4
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• pp.16-25
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• 2005

In this paper, we proposed a novel algorithm combined simulated annealing and genetic algorithms for designing optimal binary phase computer generated hologram. In the process of genetic algorithm searching by block units, after the crossover and mutation operations, simulated annealing algorithm searching by pixel units is inserted. So, the performance of BPCGH was improved. Computer simulations show that the proposed combined iterative algorithm has better performance than the simulated annealing algorithm in terms of diffraction efficiency

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.2
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• pp.147-154
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• 1989

An effective placement of macro blocks having arbitrary width and height is very important in reducing the chip area and the signal delay. In this paper, we proposed a method of macro block placement to obtain the globally optimal placement using simulated annealing, and an efficient algorithm for eliminating the overlaps between the rectangular macro blocks which may remain even after the simulated annealing process is terminated. Each macro block was enlarged to take into account minimal routing area, and these macro blocks were compacted as much as possible during the placement. This procedure was implemented in C language running on MV10000/UNIX computer system, and good placements were obtained by applying this procedure to two circuits which were consisted of 50 and 160 macro blocks respectively. Several parameters giving great effects to final placements were investigated.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.797-802
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• 2000

Flow shop scheduling problem involves processing several jobs on common facilities where a setup time Is incurred whenever there is a switch of jobs. Practical aspect of scheduling focuses on finding a near-optimum solution within a feasible time rather than striving for a global optimum. In this paper, a hybrid meta-heuristic method called tabu-genetic algorithm(TGA) is suggested, which combines the genetic algorithm(GA) with tabu list. The experiment shows that the proposed TGA can reach the optimum solution with higher probability than GA or SA(Simulated Annealing) in less time than TS(Tabu Search). It also shows that consideration of setup time becomes more important as the ratio of setup time to processing time increases.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.520-525
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• 2003

The determination of unknown parameters in rotating machinery is a difficult task and optimization techniques represent an alternative technique for parameter identification. The Simulated Annealing(SA) and Genetic Algorithm(GA) are powerful global optimization algorithm. This paper proposes new hybrid algorithm which combined GA with SA and local search algorithm for the purpose of parameter identification. Numerical examples are also presented to verify the efficiency of proposed algorithm. And, this paper presents the general methodology based on hybrid algorithm to identify unknown bearing parameters of flexible rotors using measured unbalance responses. Numerical examples are used to ilustrate the methodology used, which is then validated experimentally.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.349-356
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• 2004

In this paper, a practical image security system using SA algorithm and 4-f optical correlator system is proposed. The encrypted image and key image with binary phase components are generated using an iterative SA algorithm. a decrypted image is found through the correlation of the encrypted and key images using 4-f optical correlator system. The encrypted and key images are consisted of binary phase components. So, it is easy to implement the optical security system using the proposed technique. And if we fix the encrypted image in the optical security system and change the key images, we get different images, so it is possible to apply to the distinguished authorization system using different key images. Computer simulations show that despite the binary phase components of the two images(encrypted and key image), decrypted images are generated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1243-1252
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• 2005

A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.59-69
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• 1996

The criteria for construction of D-optimal design in nonlinear models are derived. The procedures for finding these optimal designs using the simulated annealing algorithm are presented. It is claimed that the advantages of this method are its ability to make the given data useful by adding new observations as well as to obtain a new set of appropriate data when the model and parameters are known. Research so far indicates that there has never been a case in which there is more than one independent variable but this method can be used for such cases. The result indicates the effectiveness of the method using simulated annealing algorithm for situations in which there are many independent variables and the ranges of design spaces are wide.

• IE interfaces
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• v.17 no.spc
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• pp.69-78
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• 2004

This paper presents a simulated algorithm(SA) for the optimal reliability design problem of a series system with multiple component choices incorporated at each subsystem. The objective of the problem is to maximize the system reliability while satisfying some constraint on system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. The SA algorithm is developed by introducing some solution-improvements methods. Numerical examples are tested and the results are compared. The results have demonstrated the efficiency and the effectiveness of the proposed SA algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1077-1084
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• 2003

The performance of simulated annealing (SA) algorithm such as solution optimality and computation time mainly depends on how to determine the SA-related parameters Several schemes have been suggested to improve the performance of SA and several parameter design methods have been utilized to select parameter values of each scheme. In this paper, we propose a new SA algorithm design method that can determine schemes as well as parameter values simultaneously The new SA algorithm design method is based on the Taguchl method which primarily selects the design parameters for a product or process to minimize the effect of noise parameters. so that the response is close to the desired target with minimum variation. To show the effectiveness of the proposed method, extensive computation experiments are conducted.