Mathematics – Optimization and Control
Scientific paper
2011-03-14
ACM Transactions on Mathematical Software, 29(4), (2003) 469-480
Mathematics
Optimization and Control
20 pages, 1 figure
Scientific paper
A procedure for generating non-differentiable, continuously differentiable, and twice continuously differentiable classes of test functions for multiextremal multidimensional box-constrained global optimization and a corresponding package of C subroutines are presented. Each test class consists of 100 functions. Test functions are generated by defining a convex quadratic function systematically distorted by polynomials in order to introduce local minima. To determine a class, the user defines the following parameters: (i) problem dimension, (ii) number of local minima, (iii) value of the global minimum, (iv) radius of the attraction region of the global minimizer, (v) distance from the global minimizer to the vertex of the quadratic function. Then, all other necessary parameters are generated randomly for all 100 functions of the class. Full information about each test function including locations and values of all local minima is supplied to the user. Partial derivatives are also generated where possible.
Gaviano Marco
Kvasov Dmitri E.
Lera Daniela
Sergeyev Yaroslav D.
No associations
LandOfFree
Software for Generation of Classes of Test Functions with Known Local and Global Minima for Global Optimization does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Software for Generation of Classes of Test Functions with Known Local and Global Minima for Global Optimization, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Software for Generation of Classes of Test Functions with Known Local and Global Minima for Global Optimization will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-259825