Name
Abstract | ||
|---|---|---|
This paper reports the results of a research effort that explores time/space tradeoffs inherent to genetic algorithms (GA). The study analyzes redundancy in the GA search space and lays out a schema for efficient utilization of record keeping in the form of a cache to minimize redundancy. The application used for evaluation of the record keeping procedure is feature selection for computer workload characterization. The experimental results demonstrate the utility of record keeping in the GA domain, and show a significant reduction in execution time with virtually the same solution quality. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13025-0_66 | IEA/AIE (2) |
Keywords | Field | DocType |
feature selection,ga domain,efficient utilization,execution time,time space tradeoffs,genetic algorithm,computer workload characterization,study analyzes redundancy,ga search space,space tradeoffs,genetic algorithms,heuristic search,search space | Heuristic,Feature selection,Workload,Cache,Computer science,Theoretical computer science,Redundancy (engineering),Execution time,Computer engineering,Schema (psychology),Genetic algorithm | Conference |
Volume | ISSN | ISBN |
6097 | 0302-9743 | 3-642-13024-0 |
Citations | PageRank | References |
1 | 0.37 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dan E. Tamir | 1 | 79 | 13.26 |
| Clara Novoa | 2 | 71 | 5.34 |
| Daniel Lowell | 3 | 27 | 2.29 |