- author = "Jerry Swan and John R. Woodward",
- title = "Semi-Automated Algorithm Design with Genetic Programming",
- year = "2015",
- editor = "Yadahiko Murata",
- address = "Sendai, Japan",
- month = "25-28 " # may,
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://sites.ieee.org/cec2015/tutorials/",
-
abstract = "This tutorial gives a methodology for the use of
constructive, generative hyper-heuristics to improve
human-designed algorithms. This methodology has been
successfully used by the presenters in a variety of
application areas. It employs Genetic Programming,
resulting in a semi-automated design process. The
tutorial provides a simple step-by-step guide,
introducing researchers to an exciting topic with many
potential applications.
In addition to presenting the underlying theory, the tutorial will give an introduction to Templar, a framework that supports Template Method Hyper-heuristics, by which an algorithm is parametrized by a collection of heuristics which are then configured automatically. This method makes effective use of Genetic Programming to tune the algorithm to some target set of problem instances. Since the supporting algorithm skeleton can be arbitrarily complex, this allows greater scalability than can be achieved by the naive application of Genetic Programming. The Templar approach turns the creation of generative hyper-heuristics into the more procedural matter of GP parameter tuning. We describe several case studies, including how to create a hyper-heuristic template for quicksort and show the effectiveness of the approach with a state-of-the-art application in which we optimize quicksort for power consumption. The tutorial is suitable for practitioners at every level, assuming only basic familiarity with metaheuristics and machine learning - some experience of genetic programming is helpful, but not a necessity.",
- notes = "Tutorial 1000-1145 hrs Mo2-2F4 CEC2015",
