When move acceptance selection hyper-heuristics outperform Metropolis and elitist evolutionary algorithms and when not-Reference-Cited by-同舟云学术

When move acceptance selection hyper-heuristics outperform Metropolis and elitist evolutionary algorithms and when not

Author:

Lissovoi Andrei,Oliveto Pietro S.^ORCID,Warwicker John Alasdair^ORCID

Funder

EPSRC

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference65 articles.

1. Runtime analysis of selection hyper-heuristics with classical learning mechanisms;Alanazi,2014

2. A Monte Carlo hyper-heuristic to optimise component placement sequencing for multi head placement machine;Ayob,2003

3. Black-box complexity of parallel search with distributed populations;Badkobeh,2015

4. An experimental study on hyper-heuristics and exam timetabling;Bilgin,2007

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