Title :
Optimal computing budget allocation for small computing budgets
Author :
LaPorte, G.J. ; Branke, Jurgen ; Chun-Hung Chen
Author_Institution :
George Mason Univ., Fairfax, VA, USA
Abstract :
In this paper, we develop an optimal computing budget allocation (OCBA) algorithm for selecting a subset of designs under the restriction of an extremely small computing budget. Such an algorithm is useful in population based Evolutionary Algorithms (EA) and other applications that seek an elite subset of designs.
Keywords :
budgeting; evolutionary computation; OCBA algorithm; design subset; evolutionary algorithms-based population; extremely small computing budget; optimal computing budget allocation; Algorithm design and analysis; Computational modeling; Current measurement; Educational institutions; Resource management; Sociology; Statistics;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2012 Winter
Conference_Location :
Berlin
Print_ISBN :
978-1-4673-4779-2
Electronic_ISBN :
0891-7736
DOI :
10.1109/WSC.2012.6465085
