Datasets
Standard Dataset
CCOp Mv: Scenarios of Brumadinho-MG and Optimized Solutions
- Citation Author(s):
-
EmersonAntunes
University of Brasilia - Submitted by:
- Emerson Antunes
- Last updated:
- Wed, 12/22/2021 - 22:07
- DOI:
- 10.21227/p4sh-5n54
- Data Format:
- Links:
- License:
191 Views- Categories:
- Keywords:
0 ratings - Please login to submit your rating.
Abstract
Map of the system's operating area. Note: access roads in black.
Instructions:
The best tutorial to use this Data Set is the paper: "Optimized solutions for deploying a militarized 4G/LTE network with maximum coverage and minimum interference".
Dataset Files
- All project files CCOpMv.zip (6.21 MB)
- Simulations for selecting the best crossover method Adjust_CrossoverMethods.py (13.69 kB)
- Simulations for selecting the best mutation method Adjust_MutationMethods.py (13.61 kB)
- Simulations for selecting the best selection method Adjust_SelectionMethods.py (13.94 kB)
- E-ALLOCATOR solution is an Exact solution based on Branch and Bound algorithm E_ALLOCATOR.py (16.81 kB)
- Graphics developed for evaluating project solutions Graphics.py (36.00 kB)
- Heuristc to benchmark Heuristic.py (12.75 kB)
- Adjustment of the hyperparameters of the M-ALLOCATOR solution Hyperas.py (9.49 kB)
- M-ALLOCATOR solution is an Metaheuristic solution based on Genetic Algorithm M_ALLOCATOR.py (16.13 kB)
- Geographical positions of installation of BTSs Scenario_Mij.py (973 bytes)
- Geographic positions of system customers Scenario_Nij.py (6.26 kB)
- Adjacency Matrices Scenario_Smnp.py (8.83 kB)
