A Methodology for Classifying Search Operators as Intensification or Diversification Heuristics
Joint Authors
Sotelo-Figueroa, Marco Aurelio
Espinal, A.
Ochoa, Gabriela
Ornelas-Rodriguez, Manuel
Soria-Alcaraz, Jorge Alberto
Rostro-Gonzalez, H.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-13
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Selection hyper-heuristics are generic search tools that dynamically choose, from a given pool, the most promising operator (low-level heuristic) to apply at each iteration of the search process.
The performance of these methods depends on the quality of the heuristic pool.
Two types of heuristics can be part of the pool: diversification heuristics, which help to escape from local optima, and intensification heuristics, which effectively exploit promising regions in the vicinity of good solutions.
An effective search strategy needs a balance between these two strategies.
However, it is not straightforward to categorize an operator as intensification or diversification heuristic on complex domains.
Therefore, we propose an automated methodology to do this classification.
This brings methodological rigor to the configuration of an iterated local search hyper-heuristic featuring diversification and intensification stages.
The methodology considers the empirical ranking of the heuristics based on an estimation of their capacity to either diversify or intensify the search.
We incorporate the proposed approach into a state-of-the-art hyper-heuristic solving two domains: course timetabling and vehicle routing.
Our results indicate improved performance, including new best-known solutions for the course timetabling problem.
American Psychological Association (APA)
Soria-Alcaraz, Jorge Alberto& Ochoa, Gabriela& Espinal, A.& Sotelo-Figueroa, Marco Aurelio& Ornelas-Rodriguez, Manuel& Rostro-Gonzalez, H.. 2020. A Methodology for Classifying Search Operators as Intensification or Diversification Heuristics. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1140031
Modern Language Association (MLA)
Soria-Alcaraz, Jorge Alberto…[et al.]. A Methodology for Classifying Search Operators as Intensification or Diversification Heuristics. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1140031
American Medical Association (AMA)
Soria-Alcaraz, Jorge Alberto& Ochoa, Gabriela& Espinal, A.& Sotelo-Figueroa, Marco Aurelio& Ornelas-Rodriguez, Manuel& Rostro-Gonzalez, H.. A Methodology for Classifying Search Operators as Intensification or Diversification Heuristics. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1140031
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1140031