Abstract | ||
---|---|---|
In genetic algorithms, the importance of the basis for representation has been well known. In this paper, we studied the effect of a good basis in binary representation, and resultantly we could show that a good basis improves the performance of search algorithms. A complicated problem space may be transformed into a linearly-separable one via a change of basis. We had experiments on search performance. Finding a good basis from all the bases may not be practical, because it takes O(2n2) time, where n is the length of a chromosome. However, we used a genetic algorithm to find a good basis, to correctly investigate how a basis affects the problem space. We also conducted experiments on the NK-landscape model as a representative computationally hard problem. Experimental results showed that changing basis by the presented genetic algorithm always leads better search performance on the NK-landscape model.
|
Year | Venue | Field |
---|---|---|
2018 | GECCO (Companion) | Mathematical optimization,Search algorithm,Computer science,Change of basis,Algorithm,General linear group,Problem space,Genetic algorithm,Binary number |
DocType | ISBN | Citations |
Conference | 978-1-4503-5764-7 | 0 |
PageRank | References | Authors |
0.34 | 2 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Junghwan Lee | 1 | 50 | 12.51 |
Yong-Hyuk Kim | 2 | 355 | 40.27 |