Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Handbook of Evolutionary Computation
Handbook of Evolutionary Computation
On checking the monotonicity of parametric interval solution of linear structural systems
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part II
Direct method for solving parametric interval linear systems with non-affine dependencies
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part II
Differential evolution applied to large scale parametric interval linear systems
LSSC'11 Proceedings of the 8th international conference on Large-Scale Scientific Computing
Enclosure for the solution set of parametric linear systems with non-affine dependencies
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part II
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Systems of parametric interval equations are encountered in many practical applications. Several methods for solving such systems have been developed during last years. Most of them produce both outer and inner interval solutions, but the amount of overestimation, resp. underestimation is not exactly known. If a solution of a parametric system is monotonic and continuous on each interval parameter, then the method of combination of endpoints of parameter intervals computes its interval hull. Recently, a few polynomial methods computing the interval hull were developed. They can be applied if some monotonicity and continouity conditions are fulfilled. To get the most accurate inner approximation of the solution set hull for problems with any bounded solution set, an evolutionary optimization method is applied.