Construction of large-scale global minimum concave quadratic test problems
Journal of Optimization Theory and Applications
More test examples for nonlinear programming codes
More test examples for nonlinear programming codes
A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Construction of test problems in quadratic bivalent programming
ACM Transactions on Mathematical Software (TOMS)
A test problem generator for the Steiner problem in graphs
ACM Transactions on Mathematical Software (TOMS)
Construction of test problems for a class of reverse convex programs
Journal of Optimization Theory and Applications
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Generating box-constrained optimization problems
ACM Transactions on Mathematical Software (TOMS)
Generation of large-scale quadratic programs for use as global optimization test problems
ACM Transactions on Mathematical Software (TOMS)
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
Test Functions with Variable Attraction Regions for GlobalOptimization Problems
Journal of Global Optimization
A Note on the Griewank Test Function
Journal of Global Optimization
Journal of Global Optimization
A new class of test functions for global optimization
Journal of Global Optimization
A Generator for Multimodal Test Functions with Multiple Global Optima
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Solving Global Optimization Problems Using MANGO
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Lipschitz and Hölder global optimization using space-filling curves
Applied Numerical Mathematics
Interfaces
A local search method for continuous global optimization
Journal of Global Optimization
An information global minimization algorithm using the local improvement technique
Journal of Global Optimization
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Study of multiscale global optimization based on parameter space partition
Journal of Global Optimization
Parallel scalable algorithms with mixed local-global strategy for global optimization problems
MTPP'10 Proceedings of the Second Russia-Taiwan conference on Methods and tools of parallel programming multicomputers
Lipschitz gradients for global optimization in a one-point-based partitioning scheme
Journal of Computational and Applied Mathematics
Lipschitz global optimization methods in control problems
Automation and Remote Control
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A procedure for generating non-differentiable, continuously differentiable, and twice continuously differentiable classes of test functions for multiextremal multidimensional box-constrained global optimization is 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.