Name
Title | ||
|---|---|---|
A hyperheuristic approach for dynamic enumeration strategy selection in constraint satisfaction |
Abstract | ||
|---|---|---|
In this work we show a framework for guiding the classical constraint programming resolution process. Such a framework allows one to measure the resolution process state in order to perform an "on the fly" replacement of strategies exhibiting poor performances. The replacement is performed depending on a quality rank, which is computed by means of a choice function. The choice function determines the performance of a given strategy in a given amount of time through a set of indicators and control parameters. The goal is to select promising strategies to achieve efficient resolution processes. The main novelty of our approach is that we reconfigure the search based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21326-7_32 | IWINAC (2) |
Keywords | Field | DocType |
poor performance,individual strategy,hyperheuristic approach,current problem,constraint satisfaction,efficient resolution process,dynamic enumeration strategy selection,resolution process state,main novelty,performance data,control parameter,classical constraint programming resolution,choice function,heuristic search,data gathering,constraint programming | Constraint satisfaction,Heuristic,Mathematical optimization,Process state,Computer science,Constraint programming,Enumeration,Artificial intelligence,Novelty,Machine learning,Choice function,Hybrid algorithm (constraint satisfaction) | Conference |
Volume | ISSN | Citations |
6687 | 0302-9743 | 17 |
PageRank | References | Authors |
0.81 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Broderick Crawford | 1 | 446 | 73.74 |
| Ricardo Soto | 2 | 134 | 8.15 |
| Carlos Castro | 3 | 255 | 29.05 |
| Eric Monfroy | 4 | 579 | 63.05 |