Skip to main content

Initial Release.

Project description

This code is to solve traveling salesman problem by using simulated annealing meta heuristic.

```
import numpy
import pytspsa


solver = pytspsa.Tsp_sa()
c = [
[0, 0],
[0, 1],
[0, 2],
[0, 3]
]
c = numpy.asarray(c, dtype=numpy.float32)
solver.set_num_nodes(4)
solver.add_by_coordinates(c)
solver.set_t_v_factor(4.0)

# solver.sa() or sa_auto_parameter() will solve the problem.
solver.sa_auto_parameter(12)

# getting result
solution = solver.getBestSolution()

print('Length={}'.format(solution.getlength()))
print('Path= {}'.format(solution.getRoute()))
```

See github page.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytspsa-0.1.14.tar.gz (18.6 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page