• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.288-289
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• 1992

The method of simulated annealing is a technique that has recently attracted significant attention as suitable for optimization problem of very large scale. If the temperature is too high, then some of the structure created by the heuristic will be destroyed and unnecessary extra work will be done. If it is too low then solution is lost, similar to the case of a quenching cooling schedule in the Simulated Annealing (SA) phase. Therefore, a crucial issue in this study is the determination of the starting temperature and cooling schedule for SA phase.

• Steel and Composite Structures
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• v.7 no.3
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• pp.201-217
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• 2007

Two combinatorial optimization algorithms, tabu search and simulated annealing, are presented for the minimum-weight design of geometrically non-linear steel plane frames. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) specification, maximum and interstorey drift constraints and size constraints for columns were imposed on frames. The stress constraints of AISC Allowable Stress Design (ASD) were also mounted in the two algorithms. The comparisons between AISC-LRFD and AISC-ASD specifications were also made while tabu search and simulated annealing were used separately. The algorithms were applied to the optimum design of three frame structures. The designs obtained using tabu search were compared to those where simulated annealing was considered. The comparisons showed that the tabu search algorithm yielded better designs with AISC-LRFD code specification.

• International Journal of CAD/CAM
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• v.12 no.1
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• pp.9-19
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• 2012

Generation of optimum planar B-spline curve in terms of minimum deviation and required fairness to approximate a target shape defined by a strip-shaped unorganized 2D point cloud is studied. It is proposed to use the location of control points as variables within the geometric optimization framework of point distance minimization. An adaptive simulated annealing heuristic optimization algorithm is developed to iteratively update an initial approximate curve towards the target shape. The new implementation comprises an adaptive cooling procedure in which the temperature change is adaptively dependent on the objective function evolution. It is shown that the proposed method results in an improved convergence speed when compared to the standard simulated annealing method. A couple of examples are included to show the applicability of the proposed method in the surface model reconstruction directly from point cloud data.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.381-386
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• 2000

Simple spring-damper-mass models have been widely used to understand whole-body vertical biodynamic response characteristics of the seated vehicle driver. However, most previous models have not considered about the non-rigid masses(wobbling masses). A simple mechanical model of seated human body developed in this study included the torso represented by a rigid and a wobbling mass. Within the 0.5-20Hz frequency range and for excitation amplitudes maintained below $5ms^{-2}$, this 4-degree-of-freedom driver model is proposed to satisfy the measured vertical vibration response characteristics defined from a synthesis of published data for subjects seated erect without backrest support. The parameters are identified by using the combinatorial optimization technique, simulated annealing method. The model response was found to be provided a closer agreement with the response characteristics than previously published models.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.256-256
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• 2000

In this parer, we present a real-time path planning algorithm which is integrated the artificial potential field(APF) and simulated annealing(SA) methods for mobile robot. The APF method in path planning has gained popularity since 1990's. It doesn't need the modeling of the complex configuration space of robot, and is easy to apply the path planning with simple computation. However, there is a major problem with APF method. It is the formation of local minima that can trap the robot before reaching its goal. So, to provide local minima recovery, we apply the SA method. The effectiveness of the proposed algorithm is verified through simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.140-140
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• 2000

Traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain. Hybridizing a genetic algorithm with other algorithms can produce better performance than both the genetic algorithm and the other algorithms. In this paper, we use random process and simulated annealing instead of mutation operator in order to get well tuned fuzzy rules. The key of this approach is to adjust both the width and the center of membership functions so that the tuned rule-based fuzzy controller can generate the desired performance. The effectiveness of the proposed algorithm is verified by computer simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.2
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• pp.137-140
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• 2004

다중 프로세서 시스템이 개발됨에 따라, 새로운 일정계획문제, 하나의 작업이 하나이상의 기계에 의해 동시에 처리되어야 하는 문제가 대두되었다. 이 연구에서는 선행관계를 가진 이러한 다중 프로세서 일정계획문제에 대해 다루어 보았다. 이 연구의 목적은 makespan을 최소화하는 일정계획을 찾는 것이다. 일반적으로 Branch and Bound 기법을 이용하여 선행관계를 가진 다중 프로세서 일정계획문제의 최적해를 찾았는데, 해의 탐색시간이 너무 오래 걸린다는 단점이 있었다. 본 연구에서는 짧은 시간 내에 최적해와 가까운 근사해를 simulated annealing(SA)방법을 이용하여 구해보았다. SA의 성능을 측정하기 위하여, SA의 CPU 처리시간과 구한 근사해를 40개의 예제문제를 통하여 Kramer의 방법의 CPU 처리시간과 최적해와 비교해 보았다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.44-53
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• 2007

Forming central warehouses for a number of stores can save costs in the continuous review inventory model due to economy of scale and information sharing. In this paper, transportation costs are included in this inventory model. Hence, the tradeoff between inventory-related costs and transportation costs is required. The main concern of this paper is to determine the number and location of central warehouses. Transportation costs are dependent on the distance from several central warehouses to each store. Hence, we develop an efficient simulated annealing algorithm using distance-based local search heuristic and merging heuristic to determine the location and the number of central warehouses. The objective of this paper is to minimize total costs such as holding, setup, penalty, and transportation costs. The performance of the proposed approach is tested by using some computational experiments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1020-1025
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• 2003

A successful design approach for noise barriers should be multidisciplinary because noise reduction goals influence both acoustical and non-acoustical considerations, such as maintenance, safety, physical construction, cost and visual impact These various barrier design options are closely related with barrier dimensions. In this study, we have proposed an optimal design method of noise barriers using simulated annealing algorithm, providing a barrier having the smallest dimension and achieving the specified noise reduction at a receiver region exposed to the industry and infrastructures, to help a successful barrier design.

• IE interfaces
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• v.12 no.1
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• pp.94-101
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• 1999

The set covering(SC) problem is the problem of covering all the rows of an $m{\times}n$ matrix of ones and zeros by a subset of columns with a minimal cost. It has many practical applications of modeling of real world problems. The SC problem has been proven to be NP-complete and many algorithms have been presented to solve the SC problem. In this paper we present hybrid simulated annealing(HSA) algorithm based on the Simulated Annealing(SA) for the SC problem. The HSA is an algorithm which combines SA with a crossover operation in a genetic algorithm and a local search method. Our experimental results show that the HSA obtains better results than SA does.