Abstract
We explore the potential of parallel tempering as a combinatorial optimization method, applying it to the traveling salesman problem. We compare simulation results of parallel tempering with a benchmark implementation of simulated annealing, and study how different choices of parameters affect the relative performance of the two methods. We find that a straightforward implementation of parallel tempering can outperform simulated annealing in several crucial respects. When parameters are chosen appropriately, both methods yield close approximation to the actual minimum distance for an instance with 200 nodes. However, parallel tempering yields more consistently accurate results when a series of independent simulations are performed. Our results suggest that parallel tempering might offer a simple but powerful alternative to simulated annealing for combinatorial optimization problems.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 539-556 |
| Number of pages | 18 |
| Journal | International Journal of Modern Physics C |
| Volume | 20 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2009 |
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Keywords
- Combinatorial optimization
- Parallel tempering
- Simulated annealing
- Traveling salesman problem
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Mathematical Physics
- Physics and Astronomy(all)
- Computer Science Applications
- Computational Theory and Mathematics
Cite this
Parallel tempering for the traveling salesman problem. / Wang, Chiaming; Hyman, Jeffrey D.; Percus, Allon; Caflisch, Russel.
In: International Journal of Modern Physics C, Vol. 20, No. 4, 04.2009, p. 539-556.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Parallel tempering for the traveling salesman problem
AU - Wang, Chiaming
AU - Hyman, Jeffrey D.
AU - Percus, Allon
AU - Caflisch, Russel
PY - 2009/4
Y1 - 2009/4
N2 - We explore the potential of parallel tempering as a combinatorial optimization method, applying it to the traveling salesman problem. We compare simulation results of parallel tempering with a benchmark implementation of simulated annealing, and study how different choices of parameters affect the relative performance of the two methods. We find that a straightforward implementation of parallel tempering can outperform simulated annealing in several crucial respects. When parameters are chosen appropriately, both methods yield close approximation to the actual minimum distance for an instance with 200 nodes. However, parallel tempering yields more consistently accurate results when a series of independent simulations are performed. Our results suggest that parallel tempering might offer a simple but powerful alternative to simulated annealing for combinatorial optimization problems.
AB - We explore the potential of parallel tempering as a combinatorial optimization method, applying it to the traveling salesman problem. We compare simulation results of parallel tempering with a benchmark implementation of simulated annealing, and study how different choices of parameters affect the relative performance of the two methods. We find that a straightforward implementation of parallel tempering can outperform simulated annealing in several crucial respects. When parameters are chosen appropriately, both methods yield close approximation to the actual minimum distance for an instance with 200 nodes. However, parallel tempering yields more consistently accurate results when a series of independent simulations are performed. Our results suggest that parallel tempering might offer a simple but powerful alternative to simulated annealing for combinatorial optimization problems.
KW - Combinatorial optimization
KW - Parallel tempering
KW - Simulated annealing
KW - Traveling salesman problem
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U2 - 10.1142/S0129183109013893
DO - 10.1142/S0129183109013893
M3 - Article
AN - SCOPUS:67649390954
VL - 20
SP - 539
EP - 556
JO - International Journal of Modern Physics C
JF - International Journal of Modern Physics C
SN - 0129-1831
IS - 4
ER -