The Library
On using surrogates with genetic programming
Tools
Hildebrandt, Torsten and Branke, Jürgen (2014) On using surrogates with genetic programming. Working Paper. Warwick Business School. (Unpublished)
|
PDF
WRAP_Branke_techreport (2).pdf - Other - Requires a PDF viewer. Download (775Kb) | Preview |
Official URL: http://www.wbs.ac.uk/
Abstract
One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical representation, and therefore can not be used with the tree representation of Genetic Programming (GP). In this paper, we present a new way to use surrogate models with GP. Rather than using the genotype directly as input to the surrogate model, we propose using a phenotypic characterization. This phenotypic characterization can be computed efficiently and allows us to define approximate measures of equivalence and similarity. Using a stochastic, dynamic job shop scenario as an ex- ample of simulation-based GP with an expensive fitness evaluation, we show how these ideas can be used to construct surrogate models and improve the convergence speed and solution quality of GP.
Item Type: | Working or Discussion Paper (Working Paper) | ||||
---|---|---|---|---|---|
Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Social Sciences > Warwick Business School > Operational Research & Management Sciences Faculty of Social Sciences > Warwick Business School |
||||
Library of Congress Subject Headings (LCSH): | Genetic algorithms, Surrogate-based optimization | ||||
Publisher: | Warwick Business School | ||||
Official Date: | 14 January 2014 | ||||
Dates: |
|
||||
Number of Pages: | 25 | ||||
Institution: | University of Warwick | ||||
Status: | Not Peer Reviewed | ||||
Publication Status: | Unpublished | ||||
Funder: | Deutsche Forschungsgemeinschaft (DFG) | ||||
Grant number: | SCHO 540/17-2 (DFG) |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |