Randomized Local Extrema for Heuristic Selection in TSP
It follows from the search randomizations in space-time among candidate heuristics that the optimality of an arbitrary heuristic is unsolvable. There are a countable infinite number of theories that may be decomposed into stronger local proofs. Local inductive randomization depends on domain symmetr...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2006
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/540 http://dx.doi.org/10.1109/IRI.2006.252436 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| id |
sg-smu-ink.sis_research-1539 |
|---|---|
| record_format |
dspace |
| spelling |
sg-smu-ink.sis_research-15392010-09-24T07:00:25Z Randomized Local Extrema for Heuristic Selection in TSP LIANG, Qianhui (Althea) Rubin, S. It follows from the search randomizations in space-time among candidate heuristics that the optimality of an arbitrary heuristic is unsolvable. There are a countable infinite number of theories that may be decomposed into stronger local proofs. Local inductive randomization depends on domain symmetry for tractability. TSP problems exhibit tentative domain symmetry and potential space-time randomness in domain solution evolution. Heuristics in the domain of the TSP can be found and selected with a suitable representation, randomization, and symmetric induction with a significantly reduced time. Better representation of the TSP problem facilitates a better solution 2006-09-16T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/540 info:doi/10.1109/IRI.2006.252436 http://dx.doi.org/10.1109/IRI.2006.252436 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering |
| institution |
Singapore Management University |
| building |
SMU Libraries |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
SMU Libraries |
| collection |
InK@SMU |
| language |
English |
| topic |
Software Engineering |
| spellingShingle |
Software Engineering LIANG, Qianhui (Althea) Rubin, S. Randomized Local Extrema for Heuristic Selection in TSP |
| description |
It follows from the search randomizations in space-time among candidate heuristics that the optimality of an arbitrary heuristic is unsolvable. There are a countable infinite number of theories that may be decomposed into stronger local proofs. Local inductive randomization depends on domain symmetry for tractability. TSP problems exhibit tentative domain symmetry and potential space-time randomness in domain solution evolution. Heuristics in the domain of the TSP can be found and selected with a suitable representation, randomization, and symmetric induction with a significantly reduced time. Better representation of the TSP problem facilitates a better solution |
| format |
text |
| author |
LIANG, Qianhui (Althea) Rubin, S. |
| author_facet |
LIANG, Qianhui (Althea) Rubin, S. |
| author_sort |
LIANG, Qianhui (Althea) |
| title |
Randomized Local Extrema for Heuristic Selection in TSP |
| title_short |
Randomized Local Extrema for Heuristic Selection in TSP |
| title_full |
Randomized Local Extrema for Heuristic Selection in TSP |
| title_fullStr |
Randomized Local Extrema for Heuristic Selection in TSP |
| title_full_unstemmed |
Randomized Local Extrema for Heuristic Selection in TSP |
| title_sort |
randomized local extrema for heuristic selection in tsp |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
2006 |
| url |
https://ink.library.smu.edu.sg/sis_research/540 http://dx.doi.org/10.1109/IRI.2006.252436 |
| _version_ |
1770570467477815296 |