Optimal computing budget allocation for small computing budgets

Authors:
G. Jake LaPorte;Juergen Branke;Chun-Hung Chen
Affiliations:
George Mason University, Fairfax, VA;The University of Warwick, Coventry, UK;National Taiwan University, Taipei, Taiwan
Venue:
Proceedings of the Winter Simulation Conference
Year:
2012

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Abstract

In this paper, we develop an optimal computing budget allocation (OCBA) algorithm for selecting a sub-set 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.