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우병훈,배극윤 한국의사결정학회 2000 경영과학연구 Vol.9 No.-
The Optimization problem is to select the best of many possible design alternatives in a complex design space. Genetic Algorithms, one of numerous techniques to search optimal solution, have been successfully applied to various problem(for example, parameter tuning in expert system, structural systems with a mix of continuous integer and discrete design variables) that could not have been readily solved with more conventional computational techniques, But, Conventional Genetic Algorithms are ill defined for two classes of problems ie, parameter convergence and penalty function. Therefore, this paper developed Revised Algorithms to solve these problems, As a case study, sin function example and design of gear train are demonstrated to show the effectiveness of The two Revised Genetic Algorithms(R. G. A & H. G. A.) and one of the Revised Genetic Algorithms was more effectiveness. That's H. G. A. It has robustness and problem-independent characteristics. In the reproduction step of the H. G. A. the roulette wheel method is replaced the random search and the creeping value method is modified to improve local optimum solutions in the mutation step. The encoding and decoding procedures are replaced with the real number representation method in the H. G. A.
허성관,임승환,배극윤 대구대학교 과학기술연구소 1998 科學技術硏究 Vol.5 No.1
The purpose of a study is to obtain accurate information about the low-back pain safety at tasks of the worker. The study investigated formerly studies and ergonomic design for low-back pain safety and general prevention condition. That will based paper for a low-back pain safety of the calamity at the Korea. The results show that there are significant characteristics and trends on a low-back pain accidents. These findings identified in this study can be used to manage the a low-back pain prevention efforts.