• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.6
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• pp.1827-1835
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• 1996

This paper addresses the problem of a torch path generation for the 2D laser cutting of a stock plate nested with resular or irregular parts. Under the constaint of the relative positions of parts enforced by nesting, the developed torch path algorithm generate feasible cutting path. In this paper, the basic object is a polygon( a many-slide figure) with holes. A part may be represented as a number of line segments connected end-to-end in counterclockwise order, and formed a closed contour as requied for cutting paths. The objective is to tranverse this cutting contours with a minimum path length. This paper proposes a simulated annealing based dtorch path algorithm, that is an improved version of previously suggested TSP models. Since everypiercing point of parts is not fixed in advance, the algorithm solves as relazed optimization problem for the constraint, thich is one of the main features of the proposed algorithm. For aolving the torch path optimization problem, an efficient generation mechanism of neighborhood structure and as annealing shedule were introduced. In this way, a global solution can be obtained in a reasonable time. Seveeral examples are represented to ilustrate the method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.104-108
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• 2003

Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.624-627
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• 1992

Mathematical modeling is majorly divided into three parts: the derivation of models, the fitting of models to data, and the simulation of data from models. This paper focuses on the parameter optimization which is necessary for the fitting of models to data. The method of simulated annealing(SA) 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 SA phase. In this study, therfore, we propose a technique of determination of the starting temperature and cooling schedule for SA phase.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.105-114
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• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.115-122
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• 2003

A Metropolis genetic algorithm(MGA) is developed and applied for the structural design optimization. In MGA favorable features of Metropolis algorithm in simulated annealing(SA) are incorporated in simple genetic algorithm(SGA), so that the MGA alleviates the disadvantage of finding imprecise solution in SGA and time-consuming computation in SA. Performances of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro genetic algorithm(μGA), and Kirkpatrick's SA. Typical numerical examples are used to evaluate the favorable features and applicability of MGA From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA is a reliable and efficient tool for structural design optimization.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.416-421
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• 2008

A Metropolis genetic algorithm (MGA) is a newly-developed hybrid algorithm combining simple genetic algorithm (SGA) and simulated annealing (SA). In the algorithm, favorable features of Metropolis criterion of SA are incorporated in the reproduction operations of SGA. This way, MGA alleviates the disadvantages of finding imprecise solution in SGA and time-consuming computation in SA. It has been successfully applied and the efficiency has been verified for the practical structural design optimization. However, applicability of MGA for the wider range of problems should be rigorously proved through the solution of mathematical optimization problems. Thus, performances of MGA for the typical mathematical problems are investigated and compared with those of conventional algorithms such as SGA, micro genetic algorithm (${\mu}GA$), and SA. And, for better application of MGA, the effects of acceptance level are also presented. From numerical Study, it is again verified that MGA is more efficient and robust than SA, SGA and ${\mu}GA$ in the solution of mathematical optimization problems having various features.

• Journal of the Korean Society of Marine Environment & Safety
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• v.5 no.2
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• pp.87-97
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• 1999

This study is concerned with developing a hybrid heuristic algorithm for solving the redundancy optimization problem which is very important in system safety, This study develops a HH(Hybrid Heuristic) method combined with two strategies to alleviate the risks of being trapped at a local optimum. One of them is to construct the populations of the initial solutions randomly. The other is the additional search with SA(Simulated Annealing) method in final step. Computational results indicate that HH performs consistently better than the KY method proposed in Kim[8]. Therefore, the proposed HH is believed to an attractive to other heuristic methods.

• Proceedings of the Optical Society of Korea Conference
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• 2003.02a
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• pp.242-243
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• 2003

A CGH is a hologram generated by computer. It is widely applied to wavefront manipulation, synthesis, optical information processing and interferometer. Some methods have been used to determine the optimum phase pattern to achieve high diffraction efficiency and uniform intensity such as DBS (Direct Binary Search), SA (Simulated Annealing), GA(Genetic Algorithm). These methods require long computation time to generate a hologram. (omitted)

• The Korean Journal of Rheology
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• v.10 no.2
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• pp.113-120
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• 1998

사출성형공정은 대표적인 고분자 가공공정으로 그 복잡한 특성으로 인하여 공정변 수를 최적화하는 것을 주로 경험에 의존해 왔다. 본 연구에서는 사출성형공정의 보압과정 중에 보압의 이력을 최적화하여 제품각 부분의 부피수축율차이를 최소가 되게 하는 최적화 시스템을 개발하였다. 최적화 알고리즘으로는 GA방법을 사용하였으며 본 연구에서 제안한 최적화 시스템으로 보압과정의 최적화를 수행한 결과 부피수축율의 차이가 현저히 감소하는 것을 알수 있었다. 특히 SA방법을 사용하는 경우 초기의 최적화 속도가 GA를 사용하는 경 우에 비해서 뛰어남을 알수 있었다. 또한 충전과정과 보압과정을 함께 최적화하여 보압과정 만 최적화한 결과와 비교하여 보았다.

• Tunnel and Underground Space
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• v.17 no.6
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• pp.493-502
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• 2007

Measurements of hydraulic conductivity are point or interval values, and are highly limited in their number. Meanwhile, results of geophysical prospecting can provide the information of spatial variation of geology, and abundant in number. In this study, it was aimed to develop a data integration tool for constructing a hydraulic conductivity map by integrating geophysical data and hydraulic conductivity measurements. The developed code employed a geostatistical optimization method, simulated annealing (SA), and consists of 4 distinct computation modules by which from exploratory data analysis to postprocessing of the simulation were processed. All these modules are equipped with Graphical User Interface (GUI). Validation of the developed code was evaluated in-situ in characterizing hydraulic characteristics of highly permeable fractured zone.