Name
Abstract | ||
|---|---|---|
In this work, we present our submission for the Cross-domain Heuristic Search Challenge 2011. We implemented a stochastic local search algorithm that consists of several algorithm schemata that have been offline-tuned on four sample problem domains. The schemata are based on all families of low-level heuristics available in the framework used in the competition with the exception of crossover heuristics. Our algorithm goes through an initial phase that filters dominated low-level heuristics, followed by an algorithm schemata selection implemented in a race. The winning schema is run for the remaining computation time. Our algorithm ranked seventh in the competition results. In this paper, we present the results obtained after a more careful tuning, and a different combination of algorithm schemata included in the final algorithm design. This improved version would rank fourth in the competition. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-34413-8_8 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
different combination,cross-domain heuristic search challenge,non-adaptive stochastic local search,low-level heuristics,algorithm schema,crossover heuristics,stochastic local search algorithm,final algorithm design,careful tuning,algorithm schemata selection,competition result | Problem domain,Computer science,Heuristics,Travelling salesman problem,Artificial intelligence,Schema (psychology),Distributed computing,Mathematical optimization,Heuristic,Crossover,Algorithm design,Local search (optimization),Machine learning | Conference |
Citations | PageRank | References |
2 | 0.41 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Franco Mascia | 1 | 96 | 7.24 |
| thomas stutzle | 2 | 5684 | 352.15 |