• IE interfaces
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• v.21 no.3
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• pp.254-261
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• 2008

Connected-(r,s)-out of-(m,n) : F system is an important topic in redundancy design of the complex system reliability and it's maintenance policy. Previous studies applied Monte Carlo simulation and genetic, simulated annealing algorithms to tackle the difficulty of maintenance policy problem. These algorithms suggested most suitable maintenance cycle to optimize maintenance pattern of connected-(r,s)-out of-(m,n) : F system. However, genetic algorithm is required long execution time relatively and simulated annealing has improved computational time but rather poor solutions. In this paper, we propose the ant colony optimization approach for connected-(r,s)-out of-(m,n) : F system that determines maintenance cycle and minimum unit cost. Computational results prove that ant colony optimization algorithm is superior to genetic algorithm, simulated annealing and tabu search in both execution time and quality of solution.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.42-48
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• 2002

Placement is an important step in the physical design of VLSI circuits. It is the problem of placing a set of circuit modules on a chip to optimize the circuit performance. The most popular algorithms for placement include the cluster growth, simulated annealing and integer linear programming. In this paper we propose a genetic algorithm searching solution space for the placement problem, and then compare it with simulated annealing by analyzing the results of each implementation.

• Journal of the Korea Computer Graphics Society
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• v.4 no.1
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• pp.31-40
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• 1998

Active Contour Model(ACM) is an efficient method for segmenting an object. The main shortcoming of ACM is that its result is very dependent on the shape and location of an initial contour. To overcome this shortcoming, a new segmentation algorithm is proposed in this paper. The proposed algorithm uses B-splines to describe the active contour and applies Simulated Annealing (SA) and Genetic Algorithm(GA) as energy minimization techniques. We tried to overcome the initialization problem of traditional ACM and compared the result of ACM using GA and that using SA with 2D synthetic binary images. CT and MR images.

• Journal of Korean Society of Steel Construction
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• v.12 no.6
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• pp.629-638
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• 2000

With the positive features of simulated annealing algorithms such as simplicity of the algorithm and the possibility of finding global optimum solution, SA algorithm has been widely applied to structural optimization problems. However, the algorithms are far from practical applications in structural design or optimization of building structures due to requirement of a large number of iterations and dependency on cooling schedule and stopping criteria. In this paper, with the modification of annealing process and stopping criteria, a MSA algorithm is presented in the form of two phase annealing process for optimal seismic design of braced structures. The performance of the proposed algorithm has been illustrated in detail.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.464-469
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• 1999

Recently, the need for designing multi-stage gear drive has been increased as the hear drives are used more in the applications with high-speed and small volume. The design of multi-stage gear drives includes not only dimensional design but also configuration design of various machine elements. Until now, however, the researches on the design of gear drives are mainly focused on the single-stage gear drives and the design practices for multi-stage gear drives, especially in configuration design activity, mainly depend on the experiences and 'sense' of the designer by trial and error. We propose a design algorithm to automate the dimension design and the configuration design of multi-stage gear drives. The design process consists of four steps. The number of stage should be determined in the first step. In second step, the gear ratios of each reduction stage are determined using random search, and the ratios are basic input for the dimension design of gears, which is performed by the exhaustive search in third step. The designs of gears are guaranteed by the pitting resistance and bending strength rating practices by AGMA rating formulas. In configuration design, the positions of gears are determined to minimize the volume of gearbox using simulated annealing algorithm. The effectiveness of the algorithm is assured by the design example of a 4-stage gear drive.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.2
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• pp.189-197
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• 2008

This study presents optimal compensation algorithm of differential column shortening for more than two column groups. The proposed algorithm produces the minimum story groups and their compensation thicknesses which satisfy constraint conditions on performance and construction and enables not only the relative compensation but also the mixed compensation considering absolute shortening. The simulated annealing algorithm is used as the main optimization technique. The applicability of the proposed algorithm was verified by applying it to the 61-storey building where compensation of differential column shortening had already been performed. Using, the proposed algorithm compensation was performed easily and the number of compensation was less than the field method.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1304-1310
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• 2021

Two-phase flow, especially gas-liquid two-phase flow, has a wide application in industrial field. The diagnosis of two-phase flow parameters, which directly determine the flow and heat transfer characteristics, plays an important role in providing the design reference and ensuring the security of online operation of two-phase flow system. Computer tomography (CT) is a good way to diagnose such parameters with imaging method. This paper has proposed a novel image reconstruction method for thermal neutron CT of two-phase flow with improved simulated annealing (ISA) algorithm, which makes full use of the prior information of two-phase flow and the advantage of stochastic searching algorithm. The reconstruction results demonstrate that its reconstruction accuracy is much higher than that of the reconstruction algorithm based on weighted total difference minimization with soft-threshold filtering (WTDM-STF). The proposed method can also be applied to other types of two-phase flow CT modalities (such as X(𝛄)-ray, capacitance, resistance and ultrasound).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.458-465
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• 2000

In the field of structural optimization simulated annealing (SA) algorithm has widely been adopted as an optimizer with the positive features of SA such as simplicity of the algorithm and possibility of finding global solution However, annealing process of SA algorithm based on random generator with the zeroth order structural information requires a large of number of iterations highly depending on cooling schedules and stopping criteria. In this paper, MSA algorithm is presented in the form of two phase annealing process with the effective cooling schedule and stopping criteria. With the application to optimal seismic design of steel structures, the performance of the proposed MSA algorithm has been demonstrated with respect to stability and global convergence of the algorithm

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.5
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• pp.499-505
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• 2003

In the design of mobile wireless communication system, base station location is one of the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively fur global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.513-516
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• 2002

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.