Fixed Budget Performance of the (1+1) EA on Linear Functions
Fixed Budget Performance of the (1+1) EA on Linear Functions
复制标题
(1 1) EA 在线性函数上的固定预算性能
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
N. Spooner
中科院分区：
文献类型：
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作者：
J. Lengler;N. Spooner
We present a fixed budget analysis of the (1+1) evolutionary algorithm for general linear functions, considering both the quality of the solution after a predetermined 'budget' of fitness function evaluations (a priori) and the improvement in quality when the algorithm is given additional budget, given the quality of the current solution (a posteriori). Two methods are presented: one based on drift analysis, the other on the differential equation method and Chebyshev's inequality. While the first method is superior for general linear functions, the second can be more precise for specific functions and provides concentration guarantees. As an example, we provide tight a posteriori fixed budget results for the function OneMax.
影响因子：
1.1
作者：
Benjamin Doerr;L. A. Goldberg
通讯作者：
Benjamin Doerr;L. A. Goldberg