Title :
Adaptive differential evolution and exponential crossover
Author_Institution :
Dept. of Comput. Sci., Univ. of Ostrava, Ostrava
Abstract :
Several adaptive variants of differential evolution are described and compared in two sets of benchmark problems. The influence of exponential crossover on efficiency of the search is studied. The use of both types of crossover together makes the algorithms more robust. Such algorithms are convenient for the real-world problems, where we need an adaptive algorithm applicable without time-wasting parameter tuning.
Keywords :
evolutionary computation; optimisation; adaptive algorithms; differential evolution; exponential crossover; time-wasting parameter tuning; Adaptive algorithm; Chromium; Computer science; Constraint optimization; Evolutionary computation; Genetic mutations; Helium; Information technology; Robustness;
Conference_Titel :
Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on
Conference_Location :
Wisia
Print_ISBN :
978-83-60810-14-9
DOI :
10.1109/IMCSIT.2008.4747353
