Title of article :
MinFinder: Locating all the local minima of a function Original Research Article
Author/Authors :
Ioannis G. Tsoulos، نويسنده , , Isaac E. Lagaris، نويسنده ,
Issue Information :
دوهفته نامه با شماره پیاپی سال 2006
Abstract :
A new stochastic clustering algorithm is introduced that aims to locate all the local minima of a multidimensional continuous and differentiable function inside a bounded domain. The accompanying software (MinFinder) is written in ANSI C++. However, the user may code his objective function either in C++, C or Fortran 77. We compare the performance of this new method to the performance of Multistart and Topographical Multilevel Single Linkage Clustering on a set of benchmark problems.
Keywords :
Region of attraction , Clustering , Global optimization , Stochastic methods , Monte Carlo
Journal title :
Computer Physics Communications
Journal title :
Computer Physics Communications