A Global Optimization Algorithm Using Stochastic Differential Equations.
Abstract
SIGMA is a set of FORTRAN subprograms for solving the global optimization problem, which implement a method founded on the numerical solution of a Cauchy problem for stochastic differential equations inspired by quantum physics. This paper gives a detailed description of the method as implemented in SIGMA, and reports on the numerical tests which have been performed while the SIGMA package is described in the accompanying Algorithm. The main conclusions are that SIGMA performs very well on several hard test problems; unfortunately given the state of the mathematical software for global optimization it has not been possible to make conclusive comparisons with other packages. Keywords: Algorithms, Theory, Verification, Global Optimization, Stochastic Differential Equations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 1985
- Accession Number
- ADA153526
Entities
People
- F. Aluffi-pentini
- F. Zirilli
- V. Parisi
Organizations
- University of Wisconsin–Madison