Paper Info
Title
Hyperion2: a toolkit for {meta-, hyper-} heuristic research
Abstract
In order for appropriate meta-heuristics to be chosen and tuned for specific problems, it is critical that we better understand the problems themselves and how algorithms solve them. This is particularly important as we seek to automate the process of choosing and tuning algorithms and their operators via hyper-heuristics. If meta-heuristics are viewed as sampling algorithms, they can be classified by the trajectory taken through the search space. We term this trajectory a trace. In this paper, we present Hyperion2, a Java™ framework for meta- and hyper- heuristics which allows the analysis of the trace taken by an algorithm and its constituent components through the search space. Built with the principles of interoperability, generality and efficiency, we intend that this framework will be a useful aid to scientific research in this domain.
Year
DOI
Venue
2014
10.1145/2598394.2605687
GECCO (Companion)
Keywords
Field
DocType
experimental framework,metaheuristics,analysis,hyper-heuristics,object-oriented programming,heuristic methods,search space
Mathematical optimization,Computer science,Interoperability,Hyper-heuristic,Heuristics,Operator (computer programming),Artificial intelligence,Gibbs sampling,Generality,Trajectory,Machine learning,Metaheuristic
Conference
Citations 
PageRank 
References 
0
0.34
15
Authors
4
Name
Order
Citations
PageRank
Alexander E.I. Brownlee114418.46
Jerry Swan219619.47
Ender Özcan3117962.66
Andrew J. Parkes472349.80