ACM Transactions on Mathematical Software (TOMS)
A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Proceedings of the third international conference on Genetic algorithms
Some guidelines for genetic algorithms with penalty functions
Proceedings of the third international conference on Genetic algorithms
Generalizing the notion of schema in genetic algorithms
Artificial Intelligence
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Application of a hybrid genetic algorithm to airline crew scheduling
Computers and Operations Research - Special issue: artificial intelligence, evolutionary programming and operations research
Parallel genetic algorithms with local search
Computers and Operations Research - Special issue: artificial intelligence, evolutionary programming and operations research
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
ISTASC'06 Proceedings of the 6th WSEAS International Conference on Systems Theory & Scientific Computation
A fuzzy vector valued KNN-algorithm for automatic outlier detection
Applied Soft Computing
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
EC'05 Proceedings of the 6th WSEAS international conference on Evolutionary computing
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In the present paper we apply a new Genetic Hybrid Algorithm (GHA) to globally minimize a representative set of ill-conditioned econometric/mathematical functions. The genetic algorithm was specifically designed for nonconvex mixed integer nonlinear programming problems and it can be successfully applied to both global and constrained optimization. In previous studies, we have demonstrated the efficiency of the GHA in solving complicated NLP, INLP and MINLP problems. The present study is a continuation of this research, now focusing on a set of highly irregular optimization problems. In this paper we discuss the genetic hybrid algorithm, the nonlinear problems to be solved and present the results of the empirical tests.