Multi-Method Algorithms: Investigating the Entity-to-Algorithm Allocation Problem

被引：0
|
作者：
Grobler, Jacomine [1 ]
Engelbrecht, Andries P. [2 ]
Kendall, Graham [3 ,4 ]
Yadavalli, V. S. S. [1 ]
机构：
[1] Univ Pretoria, Dept Ind & Syst Engn, ZA-0002 Pretoria, South Africa
[2] Univ Pretoria, Dept Comp Sci, Pretoria, South Africa
[3] Univ Nottingham, Sch Comp Sci, Nottingham, England
[4] Univ Nottingham, Sch Comp Sci, Semenyih, Malaysia
来源：
2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2013年
关键词：
DIFFERENTIAL EVOLUTION; ENSEMBLE;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper investigates the algorithm selection problem, otherwise referred to as the entity-to-algorithm allocation problem, within the context of three recent multi-method algorithm frameworks. A population-based algorithm portfolio, a meta-hyper-heuristic and a bandit based operator selection method are evaluated under similar conditions on a diverse set of floating-point benchmark problems. The meta-hyper heuristic is shown to outperform the other two algorithms.
引用
收藏
页码：570 / 577
页数：8
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