Abstract
Hyper-Heuristics are methods to choose and combine heuristics to generate new ones. In this work, we use a grammar-based genetic programming system as a Hyper-Heuristic framework. The framework is used for evolving effective incremental solvers for SAT (Inc*). Tests against well-known local search heuristics on a variety of benchmark problems reveal that the evolved heuristics are superior.
| Original language | English |
|---|---|
| Title of host publication | GECCO'08 |
| Subtitle of host publication | Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008 |
| Editors | Maarten Keijzer |
| Publisher | Association for Computing Machinery |
| Pages | 601-602 |
| Number of pages | 2 |
| ISBN (Print) | 9781605581309 |
| DOIs | |
| Publication status | Published - 12 Jul 2008 |
| Event | 10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 - Atlanta, GA, United States Duration: 12 Jul 2008 → 16 Jul 2008 |
Conference
| Conference | 10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008 |
|---|---|
| Country/Territory | United States |
| City | Atlanta, GA |
| Period | 12/07/08 → 16/07/08 |
Keywords
- Genetic programming
- Heuristics
- Hyper-Heuristic
- Inc*
- SAT
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