Peter Ross
Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics.
Ross, Peter; Marin-Blazquez, Javier G; Schulenburg, Sonia; Hart, Emma
Abstract
The idea underlying hyper-heuristics is to discover some
combination of familiar, straightforward heuristics that performs very well across a whole range of problems. To be worthwhile, such a combination should outperform all of the constituent heuristics. In this paper we describe a novel messy-GA-based approach that learns such a heuris-
tic combination for solving one-dimensional bin-packing problems. When applied to a large set of benchmark problems, the learned procedure finds an optimal solution for nearly 80% of them, and for the rest produces an
answer very close to optimal. When compared with its own constituent heuristics, it ranks first in 98% of the problems.
Conference Name | Genetic and Evolutionary Computation Conference (GECCO) 2003 |
---|---|
Start Date | Jul 12, 2003 |
End Date | Jul 16, 2003 |
Publication Date | Jul 12, 2003 |
Deposit Date | Jun 2, 2008 |
Peer Reviewed | Peer Reviewed |
Pages | 1295-1306 |
Keywords | Computer programming; Problem solving; Hyper-heuristics; Genetic algorithms; Bin-packing; Unidimensional; |
Public URL | http://researchrepository.napier.ac.uk/id/eprint/1844 |
You might also like
Controlling a simulated Khepera with an XCS classifier system with memory.
(2003)
Presentation / Conference Contribution
Evolutionary scheduling: a review.
(2005)
Journal Article
Hyper-heuristics.
(2005)
Book Chapter
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search