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- QAP Problem instance generation
- ===============================
- To define our quadratic assignment problem instance, we will use the available mQAP_ multi-objective quadratic problem generator.
- Genration of the instance
- ~~~~~~~~~~~~~~~~~~~~~~~~~
- We will limit ourselves here to a single objective for the purposes of this example. The file **makeQAPuni.cc**, will be used to generate the instance.
- .. code:: bash
- g++ makeQAPuni.cc -o mQAPGenerator
- ./mQAPGenerator -n 100 -k 1 -f 30 -d 80 -s 42 > qap_instance.txt
- with the following parameters:
- - **-n** positive integer: number of facilities/locations;
- - **-k** positive integer: number of objectives;
- - **-f** positive integer: maximum flow between facilities;
- - **-d** positive integer: maximum distance between locations;
- - **-s** positive long: random seed.
- The generated qap_instance.txt_ file contains the two matrices :math:`F` and :math:`D` and define our instance problem.
- .. _mQAP: https://www.cs.bham.ac.uk/~jdk/mQAP/
- .. _qap_instance.txt: https://github.com/jbuisine/macop/blob/master/examples/instances/qap/qap_instance.txt
- Load data instance
- ~~~~~~~~~~~~~~~~~~
- We are now going to load this instance via a Python code which will be useful to us later on:
- .. code:: Python
- qap_instance_file = 'qap_instance.txt'
- n = 100 # the instance size
- with open(qap_instance_file, 'r') as f:
- file_data = f.readlines()
- print(f'Instance information {file_data[0]}')
- D_lines = file_data[1:n + 1]
- D_data = ''.join(D_lines).replace('\n', '')
- F_lines = file_data[n:2 * n + 1]
- F_data = ''.join(F_lines).replace('\n', '')
- D_matrix = np.fromstring(D_data, dtype=float, sep=' ').reshape(n, n)
- print(f'D matrix shape: {D_matrix.shape}')
- F_matrix = np.fromstring(F_data, dtype=float, sep=' ').reshape(n, n)
- print(f'F matrix shape: {F_matrix.shape}')
- .. note::
- As we know the size of our instance and the structure of the document, it is quite quick to look for the lines related to the :math:`F` and :math:`D` matrices.
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