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 systematicaly 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..
|Number of pages||22|
|Journal||Memoirs of the Kyushu University, Faculty of Engineering|
|Publication status||Published - Sep 1 1995|
All Science Journal Classification (ASJC) codes
- Atmospheric Science
- Earth and Planetary Sciences(all)
- Management of Technology and Innovation