• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.777-786
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• 2007

This paper presents a modified simulated annealing algorithm to optimize linear scheduling projects with multiple resource constraints and its effectiveness is verified with a proposed problem. A two-stage solution-finding procedure is used to model the problem. Then the simulated annealing and the modified simulated annealing are compared in the same condition. The comparison results and the reasons of improvement by the modified simulated annealing are presented at the end.

• 한국통신학회논문지
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• 제27권3A호
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• pp.284-289
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• 2002

본 논문에서는 MRF(Markov Random field)를 이용해 영상을 분할할 때, 에너지 최적화를 위해 사용되는 simulated annealing의 수렴속도를 개선하는 방법을 제안하였다. Simulated annealing은 잡음이 포함된 영상이나, 텍스쳐 영상에서 좋은 분할 결과를 나타내지만, 수렴속도가 길다는 단점이 있다. 본 논문에서는 수렴속도를 개선하기 위해 픽셀 레이블의 초기값을 픽셀의 intensity에 따라 adaptive하게 부여하여 simulated annealing을 수행하였다. 이 방법으로 모의실험을 수행한 결과, 기존의 방법보다 수렴 속도를 크게 향상시킬 수 있었다.

• 대한기계학회논문집A
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• 제29권2호
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• pp.262-269
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• 2005

Optimization of a satellite structure under severe space launching environments is performed considering various design constraints. Simulate annealing, one of combinatorial optimization techniques, is used to optimize the satellite. The optimization results by the simulated annealing are compared to those by the method of modified feasible direction and genetic algorithm. Ten bar truss structure is optimized for feasibility study of the simulated annealing. Finally, the satellite structure is optimized by the simulated annealing algorithm under space environment. Weights of the satellite upper platform and propulsion module are minimized with consideration of several static and dynamic constraints. MSC/NASTRAN is used to find the static and dynamic responses. Simulated annealing has been programmed and integrated with the finite element analysis program for optimization. It is shown that the simulated annealing algorithm can be extended to the optimization of space structures.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집A
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• pp.939-944
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• 2001

Genetic algorithm is modelled on natural evolution and simulated annealing is based on the simulation of thermal annealing. Both genetic algorithm and simulated annealing are stochastic method. So they can find global optimum values. For compare efficiency of SA and GA's, some function value was maximized. In the result, that was a little better than GA's.

• Journal of Multimedia Information System
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• 제2권1호
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• pp.179-186
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• 2015

This paper describes the application of a simulated annealing to a random signal-based learning. The simulated annealing is used to generate the reinforcement signal which is used in the random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural network. It is poor at hill-climbing, whereas simulated annealing has an ability of probabilistic hill-climbing. Therefore, hybridizing a random signal-based learning with the simulated annealing can produce better performance than before. The validity of the proposed algorithm is confirmed by applying it to two different examples. One is finding the minimum of the nonlinear function. And the other is the optimization of fuzzy control rules using inverted pendulum.

• 한국지능시스템학회논문지
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• 제21권1호
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• pp.138-144
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• 2011

그래프 G = (V, E )의 L(2, 1)-labeling 은 무선통신에서 무선 기기에 할당되는 주파수를 효율적으로 사용하기 위한 최적화 문제로서 NP-complete 계열에 포함되는 문제이다. 본 연구에서는 L(2, 1)-labeling 문제에 적용 가능한 Simulated Annealing 알고리즘을 제시한 후 다양한 그래프에 제시된 알고리즘을 적용하여 그 효용성을 보이고자 한다.

• 정보처리학회논문지A
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• 제18A권2호
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• pp.69-74
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• 2011

그래프 G의 최소 dominating set 문제는 G의 dominating set들 중 가장 작은 크기의 dominating set을 찾는 문제이며, NP-complete class에 속해 polynomial time안에 해결할 수 없는 문제로 잘 알려져 있다. 그러나, heuristic한 방법 혹은 approximation 방법을 이용해 특정한 분야에 적용이 가능하다. 본 논문에서는 세 개의 서로 다른 simulated annealing 알고리즘을 제시하여, 이들 알고리즘을 DIMACS에서 제시한 그래프들에 적용한 경우 효율성 증가가 이루어지는 것을 실험적으로 보이고자 한다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1436-1441
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• 2003

Recently, simulated annealing algorithms have widely been applied to many structural optimization problems. In this paper, simulated annealing, boltzmann annealing, fast annealing and adaptive simulated annealing are applied to optimization of truss structures for improvement quality of objective function and number of function evaluation. These algorithms are classified by cooling schedule. The authors have changed parameters of ASA's cooling schedule and the influence of cooling schedule parameters on structural optimization obtained is discussed. In addition, cooling schedule of BA and ASA mixed is applied to 10 bar-truss structure.

• 동력기계공학회지
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• 제2권3호
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• pp.60-67
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• 1998

Edge detection is the first step and very important step in image analysis. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that evaluates the quality of edge configurations. The cost function can be used as a basis for comparing the performances of different detectors. This cost function is made of desirable characteristics of edges such as thickness, continuity, length, region dissimilarity. And we use a simulated annealing algorithm for minimum of cost function. Simulated annealing are a class of adaptive search techniques that have been intensively studied in recent years. We present five strategies for generating candidate states. Experimental results(building image and test image) which verify the usefulness of our simulated annealing approach to edge detection are better than other operator.

• 자원환경지질
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• 제28권3호
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• pp.305-309
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• 1995

There is a deep and useful connection between thermodynamics (the behavior of systems with many degrees of freedom in thermal equilibrium at a finite temperature) and combinational or continuous optimization (finding the minimum of a given multiparameter function). At the heart of the method of simulated annealing is an analogy with the way that liquids freeze and crystallize, or metals cool and anneal. This paper provides a detailed description of simulated annealing. Although computationaly intensive, when it is carefully implemented, simulated annealing is found to give superior results to more traditional methods of nonlinear optimization.