Name
Abstract | ||
|---|---|---|
Many combinatorial optimization problems provide their data in an input space with a given dimension. Genetic algorithms for those problems can benefit by using this natural dimension for the encoding of the individuals rather than a traditional one-dimensional bit string. This is true in particular if each data point of the problem corresponds to a bit or a group of bits of the chromosome. We develop different methods for constructing a rectangular grid of near-optimal dimension for given data points, providing a natural encoding of the individuals. Our algorithms are tested with some large TSP instances. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1007/3-540-45365-2_12 | EvoWorkshops |
Keywords | Field | DocType |
data points,combinatorial optimization problem,natural encoding,large tsp instance,input space,natural dimension,genetic algorithm,near-optimal dimension,data point,different method,rectangular grids,traditional one-dimensional bit string,efficient construction | Data point,Data processing,Computer science,Algorithm,Combinatorial optimization,Travelling salesman problem,Bit array,Genetic algorithm,Grid,Encoding (memory) | Conference |
Volume | ISSN | ISBN |
2037 | 0302-9743 | 3-540-41920-9 |
Citations | PageRank | References |
1 | 0.54 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jan Poland | 1 | 1 | 0.54 |
| Kosmas Knödler | 2 | 4 | 1.82 |
| Andreas Zell | 3 | 63 | 14.45 |