제어로봇시스템학회:학술대회논문집
- 1995.10a
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- Pages.14-17
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- 1995
Likelihood search method with variable division search
- Koga, Masaru (Dept. of Electrical Engineering, Kyushu Univ.) ;
- Hirasawa, Kotaro (Dept. of Electrical Engineering, Kyushu Univ.) ;
- Murata, Junichi (Dept. of Electrical Engineering, Kyushu Univ.) ;
- Ohbayashi, Masanao (Dept. of Electrical Engineering, Kyushu Univ.)
- Published : 1995.10.01
Abstract
Various methods and techniques have been proposed for solving optimization problems; the methods have been applied to various practical problems. However the methods have demerits. The demerits which should be covered are, for example, falling into local minima, or, a slow convergence speed to optimal points. In this paper, Likelihood Search Method (L.S.M.) is proposed for searching for a global optimum systematically and effectively in a single framework, which is not a combination of different methods. The L.S.M. is a sort of a random search method (R.S.M.) and thus can get out of local minima. However exploitation of gradient information makes the L.S.M. superior in convergence speed to the commonly used R.S.M..