Does Comma Selection Help To Cope With Local Optima?

被引:29
作者
Doerr, Benjamin [1 ]
机构
[1] Inst Polytech Paris, Ecole Polytech, CNRS, Lab Informat LIX, Palaiseau, France
来源
GECCO'20: PROCEEDINGS OF THE 2020 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE | 2020年
关键词
Comma selection; runtime analysis; theory; OFFSPRING POPULATION-SIZE; LEVEL-BASED ANALYSIS; DRIFT ANALYSIS; EVOLUTIONARY ALGORITHMS; TIME-COMPLEXITY; HITTING TIMES; RUNNING TIME; LOWER BOUNDS; CHOICE;
D O I
10.1145/3377930.3389823
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One hope of using non-elitism in evolutionary computation is that it aids leaving local optima. We perform a rigorous runtime analysis of a basic non-elitist evolutionary algorithm (EA), the (mu, lambda) EA, on the most basic benchmark function with a local optimum, the jump function. We prove that for all reasonable values of the parameters and the problem, the expected runtime of the (mu, lambda) EA is, apart from lower order terms, at least as large as the expected runtime of its elitist counterpart, the (mu + lambda) EA (for which we conduct the first runtime analysis to allow this comparison). Consequently, the ability of the (mu, lambda) EA to leave local optima to inferior solutions does not lead to a runtime advantage. We complement this lower bound with an upper bound that, for broad ranges of the parameters, is identical to our lower bound apart from lower order terms. This is the first runtime result for a non-elitist algorithm on a multi-modal problem that is tight apart from lower order terms.
引用
收藏
页码:1304 / 1313
页数:10
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