Likelihood based search method (L.S.M.)

Masaru Koga, Kotaro Hirasawa, Junichi Murata, Masanao Ohbayashi

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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..

Original languageEnglish
Pages (from-to)235-256
Number of pages22
JournalMemoirs of the Kyushu University, Faculty of Engineering
Issue number3
Publication statusPublished - Sept 1995

All Science Journal Classification (ASJC) codes

  • General Energy
  • Atmospheric Science
  • General Earth and Planetary Sciences
  • Management of Technology and Innovation


Dive into the research topics of 'Likelihood based search method (L.S.M.)'. Together they form a unique fingerprint.

Cite this