Title :
Threshold selection, hypothesis tests, and DOE methods
Author :
Beielstein, Thomas ; Markon, Sandor
Author_Institution :
Dept. of Comput. Sci., Dortmund Univ., Germany
Abstract :
Threshold selection-a selection mechanism for noisy evolutionary algorithms-is put into the broader context of hypothesis testing. Optimal selection thresholds were derived theoretically. These theoretical results were used to find threshold values for a simple model of stochastic search and for a simplified elevator simulator. Design of experiments methods are used to validate the significance of the results
Keywords :
design of experiments; evolutionary computation; lifts; optimisation; search problems; simulation; stochastic processes; design of experiments methods; hypothesis testing; noisy evolutionary algorithms; optimal selection thresholds; simplified elevator simulator; stochastic search; threshold selection; Computer science; Design methodology; Elevators; Evolutionary computation; Extraterrestrial measurements; Mathematical model; Noise measurement; Stochastic resonance; Testing; US Department of Energy;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1007024
