semvec/pypi-packages huggingface dataset:
tspgrasp 0.1.1
GRASP for TSP
License: Apache License 2.0
Keywords: Traveling Salesman Problem,TSP,Greedy Randomized Adaptive Search Procedures,Heuristics,Metaheuristics,Meta-heuristics,Greedy Algorithms,Local Search,Variable Neighborhood Search,Simulated Annealing

# tsp-grasp

Welcome to `tsp-grasp`! A Python package with Heuristics for solving the Traveling Salesman Problem (TSP).

[Documentation](https://tsp-grasp.readthedocs.io/en/latest/)

<p align="center">
  <img src="./assets/grasp_arc_horizontal.gif" width="600" title="icon tsp">
</p>

## Install

The package `tspgrasp` is available on PyPI, so you can install it via `pip` by running the following command line:

```
pip install tspgrasp
```

To install the package in development versions, clone it from github using:

```
git clone https://github.com/bruscalia/tsp-grasp.git
```

And run one of the two following commands:

```
pip install .
```

```
python setup.py install
```

Make sure Cython and numpy are also available in your python environment.

Alternatively, you can directly run:

```
pip install git+https://github.com/bruscalia/tsp-grasp.git
```

Here is a minimum working example in which a symmetric distance matrix is produced from 2-dimensional coordinates.

## Use

```python
# Imports
import numpy as np
from scipy.spatial.distance import pdist, squareform
from tspgrasp import Grasp
```

```python
# Create distance matrix
X = np.random.random((100, 2))
D = squareform(pdist(X))

# Instantiate algorithm and solve problem
grasp = Grasp(seed=12)
sol = grasp(D, time_limit=10, max_iter=100)

# Display cost and tour
print(f"Cost: {sol.cost}")
print(f"Tour: {sol.tour}")
```

## Theory

Greedy Randomized Adaptive Search Procedures (GRASP) are metaheuristics constituted by a hybridization of a semi-greedy procedure with a local search method. For more details please refer to Resende & Ribeiro (2016).

Local search moves implemented were based on the work of Vidal (2022).


## Contact

You can reach out to me at bruscalia12@gmail.com

## References

Resende, M. G., & Ribeiro, C. C. (2016). Optimization by GRASP. Springer Science+ Business Media New York. https://doi.org/10.1007/978-1-4939-6530-4

Vidal, T. (2022). Hybrid genetic search for the CVRP: Open-source implementation and SWAP* neighborhood. Computers & Operations Research, 140, 105643. https://doi.org/10.1016/j.cor.2021.105643
tencentcloud-sdk-python-casb 3.0.1033
Tencent Cloud Casb SDK for Python
License: Apache License 2.0

============================
Tencent Cloud SDK for Python
============================

Tencent Cloud Python Casb SDK is the official software development kit, which allows Python developers to write software that makes use of Tencent Cloud services like CVM and CBS.
The SDK works on Python versions:

   * 2.7 and greater, including 3.x

Quick Start
-----------

First, install the library:

.. code-block:: sh

    $ pip install tencentcloud-sdk-python-common
    $ pip install tencentcloud-sdk-python-casb

or download source code from github and install:

.. code-block:: sh

    $ git clone https://github.com/tencentcloud/tencentcloud-sdk-python.git
    $ cd tencentcloud-sdk-python
    $ python package.py --components common casb