NUMERICAL EXPERIMENTS ON QUADRATICALLY CONVERGENT ALGORITHMS FOR FUNCTION MINIMIZATION,
Abstract
The nine quadratically convergent algorithms for function minimization which appeared in another paper by Huang are tested through several numerical examples. Three quadratic functions and four nonquadratic functions are investigated. For the quadratic functions, the results show that, if high-precision arithmetic together with high accuracy in the one-dimensional search is employed, all the algorithms behave identically: they all produce the same sequence of points and they all lead to the minimal point in the same number of iterations (this number is equal at most to the number of variables). For the nonquadratic functions, the results show that some of the algorithms behave identically and, therefore, any one of them can be considered to be representative of the entire class. The effect of different restarting conditions on the convergence characteristics of the algorithms is studied. Proper restarting conditions for faster convergence are given. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1969
- Accession Number
- AD0707585
Entities
People
- Alejandro V. Levy
- Ho-yi Huang
Organizations
- Rice University