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Repository for paper Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
Database		Database
Discretization		Discretization
Instances		Instances
MachineLearning		MachineLearning
Metaheuristics		Metaheuristics
Metrics		Metrics
Problem		Problem
Solver		Solver
__pycache__		__pycache__
.gitattributes		.gitattributes
1.- configure (con 80a BQSA) copy.py		1.- configure (con 80a BQSA) copy.py
2.- configure (con 40a BQSA).py		2.- configure (con 40a BQSA).py
README.md		README.md
db_config.ini		db_config.ini
main.py		main.py
settings.py		settings.py

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BSS-BQSA

Work repository for "Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector"

Instructions

1) Create PostgreSQL Database (file and scripts to create a data bases in local postgres are in file "Table_DB_mh_resultados.sql")

2) Update "db_config.ini" with the credentials corresponding to the created database.

3) Install the settings.py for install all packages and set up the envir

4) Populate database with the experiments to be performed in "configure.py". You can follow the example with the "1.- configure (con 80a BQSA).py" file.

python configure.py

5) Running experiments

python main.py

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Repository for paper Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector

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