| 1 |
Physical Optimization applies a set of Optimization (minimization) methods motivated by physical processes to general optimization problems
|
| 2 |
These include simulated annealing, neural networks, deterministic annealing, simulated tempering and genetic algorithms
|
| 3 |
We look at general TSP, clustering in physical spaces, track finding, navigation, school class scheduling, Random field Ising Models and data decomposition and other computing optimization problems
|
| 4 |
We discuss when methods such as neural networks are effective
|
