• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.183-186
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• 1995

A method is presented for optimization of Universal Learning Networks (ULN), where, together with gradient method, Simulated Annealing (SA) is employed to elude local minima. The effectiveness of the method is shown by its application to control of a crane system.

• 제어로봇시스템학회논문지
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• 제7권10호
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• pp.819-826
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• 2001

Genetic algorithms are becoming more popular because of their relative simplicity and robustness. Genetic algorithms are global search techniques for nonlinear optimization. However, traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain because they are poor at hill-climbing, whereas simulated annealing has the ability of probabilistic hill-climbing. Therefore, hybridizing a genetic algorithm with other algorithms can produce better performance than using the genetic algorithm or other algorithms independently. In this paper, we propose an efficient hybrid optimization algorithm named the adaptive random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural networks. This paper describes the application of genetic algorithms and simulated annealing to a random signal-based learning in order to generate the parameters and reinforcement signal of the random signal-based learning, respectively. The validity of the proposed algorithm is confirmed by applying it to two different examples.

• Steel and Composite Structures
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• 제7권3호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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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.

• 산업공학
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• 제12권1호
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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.

• 동력기계공학회지
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• 제8권2호
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• pp.45-52
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• 2004

This paper describes the optimum design for journal bearings by using simulated annealing method. Simulated annealing algorithm is an optimization technique to calculate global and local optimum solutions. Dynamic characteristics of the journal bearing are calculated by using finite difference method (FDM), and these values are used for the procedure of journal bearing optimization. The objective is to minimize the resonance response (Q factor) of the simple rotor system supported by the journal bearings. Bearing clearance and length to diameter ratio are used as the design variables.

• 융합신호처리학회논문지
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• 제3권1호
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• pp.87-92
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• 2002

배치(Placement)는 VLSI 회로의 physical design에서 중요한 단계로서 회로의 성능을 최대로 하기 위하여 회로 모듈의 집합을 배치시키는 문제이며, 배치 문제에서 최적의 해를 얻기 위해 클러스터 성장(cluster growth), 시뮬레이티드 어닐링(simulated annealing; SA), ILP(integer linear programming)등의 방식이 이용된다. 본 논문에서는 배치 문제에 대하여 확률 진화 알고리즘(stochastic evolution algorithm; StocE)을 이용한 해 공간 탐색(solution space search) 방식을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링 방식과 비교, 분석하였다.

• 산업공학
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• 제18권4호
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• pp.370-381
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• 2005

This study is concerned with seeking the optimal allocation(disposition) for maximizing utility of consolidating old fashioned and new air defense weapon system like SAM-X(Patriot missile) and developing efficient solution algorithm based on simulated annealing(SA) algorithm. The SED(selection by effectiveness degree) procedure is implemented with an enhanced SA algorithm in which neighboring solutions could be generated only within the optimal feasible region by using a specially designed PERTURB function. Computational results conducted on the problem sets with a variety of size and parameters shows the significant efficiency of our SED algorithm over existing methods in terms of both the computation time and the solution quality.

• 한국산업정보학회논문지
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• 제10권4호
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• pp.16-25
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• 2005

본 논문에서는 최적의 이진 위상 컴퓨터형성홀로그램을 설계하기 위해 SA 및 GA를 합성한 새로운 방법을 제안하였다. 블럭단위 탐색을 하는 GA의 교배연산 및 돌연변이 연산과정 후에 화소단위의 면밀한 탐색을 하는 SA 알고리듬을 삽입하므로써 BPCGH의 성능을 개선시켰다. 컴퓨터 시뮬레이션에서 제안된 합성 반복 알고리듬이 기존의 SA 알고리듬보다 회절효율이 향상됨을 보였다.

• 한국통신학회논문지
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• 제28권5C호
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• pp.468-475
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• 2003

본 논문에서는 패턴생성을 위한 최적의 이진 위상 컴퓨터형성 홀로그램을 설계하기 위해 합성된 SA알고리듬 및 유전 알고리듬을 이용하였다. 제안된 방법의 탐색과정에서 sGA를 사용하여 BPCGH를 생성하고. 결과 홀로그램 패턴을 SA 알고리듬의 초기 랜덤 투과함수로 이용하여 최적의 BPCGH를 설계하였다. 컴퓨터 시뮬레이션에서 독립적으로 사용된 SA 알고리듬과 유전 알고리듬을 비교한 결과 제안한 알고리듬이 회절 효율이 향상된 것을 확인할 수 있었다.