Abstract
We consider a possible scenario of experimental analysis on heuristics for optimization: identifying the contribution of local search components when algorithms are evaluated on the basis of solution quality attained.
We discuss the experimental designs with special focus on the role of the test instances in the statistical analysis. Contrary to previous practice of modeling instances as a blocking factor, we treat them as a random factor. Together with algorithms, or their components, which are fixed factors, this leads naturally to a mixed ANOVA model. We motivate our choice and illustrate the application of the mixed model on a study of local search for the 2-edge-connectivity problem.
We discuss the experimental designs with special focus on the role of the test instances in the statistical analysis. Contrary to previous practice of modeling instances as a blocking factor, we treat them as a random factor. Together with algorithms, or their components, which are fixed factors, this leads naturally to a mixed ANOVA model. We motivate our choice and illustrate the application of the mixed model on a study of local search for the 2-edge-connectivity problem.
| Original language | English |
|---|---|
| Book series | Lecture Notes in Computer Science |
| Volume | 4638 |
| Pages (from-to) | 91-105 |
| Number of pages | 15 |
| ISSN | 0302-9743 |
| DOIs | |
| Publication status | Published - 2007 |