| dc.contributor.author |
Ferentinos, K |
en |
| dc.contributor.author |
Arvanitis, K |
en |
| dc.contributor.author |
Sigrimis, N |
en |
| dc.date.accessioned |
2014-06-06T06:44:55Z |
|
| dc.date.available |
2014-06-06T06:44:55Z |
|
| dc.date.issued |
2002 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.1023/A:1015527207828 |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/2151 |
|
| dc.subject |
Cost Function |
en |
| dc.subject |
Genetic Algorithm |
en |
| dc.subject |
Heuristic Optimization |
en |
| dc.subject |
Motion Planning |
en |
| dc.subject |
Simulated Annealing |
en |
| dc.subject |
Simulated Annealing Algorithm |
en |
| dc.title |
Heuristic optimization methods for motion planning of autonomous agricultural vehicles |
en |
| heal.type |
journalArticle |
en |
| heal.identifier.primary |
10.1023/A:1015527207828 |
en |
| heal.publicationDate |
2002 |
en |
| heal.abstract |
In this paper, two heuristic optimization techniques are tested and compared in the application of motion planning for autonomous agricultural vehicles: Simulated Annealing and Genetic Algorithms. Several preliminary experimentations are performed for both algorithms, so that the best neighborhood definitions and algorithm parameters are found. Then, the two tuned algorithms are run extensively, but for no more than 2000 cost |
en |
| heal.journalName |
Journal of Global Optimization |
en |
| dc.identifier.doi |
10.1023/A:1015527207828 |
en |