A hybrid heuristic for the maximum clique problem
Journal of Heuristics
Comparative study of SQP and metaheuristics for robotic manipulator design
Applied Numerical Mathematics
Hybrid Genetic Programming for Optimal Approximation of High Order and Sparse Linear Systems
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Differential evolution for solving multi-mode resource-constrained project scheduling problems
Computers and Operations Research
Model-free adaptive control design using evolutionary-neural compensator
Expert Systems with Applications: An International Journal
DE and NLP Based QPLS Algorithm
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Frequency-domain weighted RLS model reduction for complex SISO linear system
ACC'09 Proceedings of the 2009 conference on American Control Conference
Baldwinian learning in clonal selection algorithm for optimization
Information Sciences: an International Journal
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Improved differential evolution approach for optimization of surface grinding process
Expert Systems with Applications: An International Journal
Clonal selection algorithm with search space expansion scheme for global function optimization
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
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The problem of optimally approximating linear systems is solved by a differential evolution algorithm (DEA) incorporating a search-space expansion scheme. The optimal approximate rational model with/without a time delay for a system described by its rational or irrational transfer function is sought such that a frequency-domain L2-error criterion is minimized. The distinct feature of the proposed model approximation approach is that the search-space expansion scheme can enhance the possibility of converging to a global optimum in the DE search. This feature and the chosen frequency-domain error criterion make the proposed approach quite efficacious for optimally approximating unstable and/or nonmimimum-phase linear systems. The simplicity and robustness of the modified DEA in terms of easy implementation and minimum assumptions on search space are demonstrated by two numerical examples