- author = "John R. Woodward and Jerry Swan",
- title = "Template method hyper-heuristics",
- booktitle = "GECCO 2014 Workshop on Metaheuristic Design Patterns (MetaDeeP)",
- year = "2014",
- editor = "Jerry Swan and Krzysztof Krawiec and John Woodward and Chris Simons and John Clark",
- isbn13 = "978-1-4503-2881-4",
- keywords = "genetic algorithms, genetic programming, hyper-heuristic",
- pages = "1437--1438",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Vancouver, BC, Canada",
-
URL = "
http://doi.acm.org/10.1145/2598394.2609843",
-
DOI = "
doi:10.1145/2598394.2609843",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- acmid = "2609843",
- size = "2 pages",
-
abstract = "The optimisation literature is awash with
metaphorically-inspired meta-heuristics and their
subsequent variants and hybridisation. This results in
a plethora of methods, with descriptions that are often
polluted with the language of the metaphor which
inspired them [8]. Within such a fragmented field, the
traditional approach of manual 'operator tweaking'
makes it difficult to establish the contribution of
individual metaheuristic components to the overall
success of a methodology.
Irrespective of whether it happens to best the state-of-the-art, such 'tweaking' is so labour-intensive that does relatively little to advance scientific understanding. In order to introduce further structure and rigour, it is therefore desirable to not only to be able to specify entire families of metaheuristics (rather than individual metaheuristics), but also be able to generate and test them. In particular, the adoption of a model agnostic approach towards the generation of metaheuristics would help to establish which metaheuristic components are useful contributors to a solution.",
- notes = "Also known as \cite{2609843} \cite{Woodward:2014:TMH:2598394.2609843} Distributed at GECCO-2014.",
