| dc.creator |
Pizlo, Zygmunt |
|
| dc.creator |
Stefanov, Emil |
|
| dc.creator |
Saalweachter, John |
|
| dc.creator |
Li, Zheng |
|
| dc.creator |
Haxhimusa, Yll |
|
| dc.creator |
Kropatsch, Walter G. |
|
| dc.date |
2006-12-05T21:05:40Z |
|
| dc.date.accessioned |
2015-07-24T14:18:14Z |
|
| dc.date.available |
2015-07-24T14:18:14Z |
|
| dc.identifier |
http://docs.lib.purdue.edu/jps/vol1/iss1/8 |
|
| dc.identifier |
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1009&context=jps |
|
| dc.identifier.uri |
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1009&context=jps |
|
| dc.identifier.uri |
http://evidence.thinkportal.org/handle/123456789/25609 |
|
| dc.description |
We tested human performance on the Euclidean Traveling Salesman Problem using problems with 6 to 50 cities. Results confirmed our earlier findings that: (a) the time of solving a problem is proportional to the number of cities, and (b) the solution error grows very slowly with the number of cities. We formulated a new version of a pyramid model. The new model has an adaptive spatial structure, and it simulates visual acuity and visual attention. Specifically, the model solves the E-TSP problem sequentially by moving attention from city to city, the same way human subjects do. The model includes a parameter representing the magnitude of local search. This parameter allows modeling individual differences among the subjects. The computational complexity of the current implementation of the model is O(n2), but this can most likely be improved to O[nlog(n)]. Simulation experiments demonstrated psychological plausibility of the new model. |
|
| dc.format |
application/pdf |
|
| dc.publisher |
Purdue University |
|
| dc.source |
The Journal of Problem Solving |
|
| dc.title |
Traveling Salesman Problem: A Foveating Pyramid Model |
|
| dc.type |
Article |
|