Abstract
This paper studies two landscapes of different instances of the 0-1 knapsack problem. The instances are generated randomly from varied weight distributions. We show that the variation of the weights can be used to guide the selection of the most suitable local search operator for a given instance.
| Original language | English |
|---|---|
| Title of host publication | GECCO Companion '15 |
| Subtitle of host publication | Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation |
| Publisher | Association for Computing Machinery |
| Pages | 1343-1344 |
| Number of pages | 2 |
| ISBN (Print) | 978-1450334884 |
| DOIs | |
| Publication status | Published - 11 Jul 2015 |
| Event | 17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain Duration: 11 Jul 2015 → 15 Jul 2015 |
Conference
| Conference | 17th Genetic and Evolutionary Computation Conference, GECCO 2015 |
|---|---|
| Country/Territory | Spain |
| City | Madrid |
| Period | 11/07/15 → 15/07/15 |
Keywords
- Constraint handling
- Fitness landscapes
- Instance difficulty
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Artificial Intelligence