Python implemetations (sequential and parallel) of the semi autonomous particle swarm optmizer (sapso)
1- Define your parameters of optmization in a dictionary as specified in the example
2- Call the optmizer of your choice passing those parameters:
from psapso.optmizer import sapso
sapso(parameters)
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/sapso:
SAPSO basic implementation, allows to chose between sequential and parallel gradient calculation
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/psapso:
Parallel SAPSO beta implementation
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/psapso slow_info_exchange:
Parallel SAPSO based on slow informaitone exchange beta implementation
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/scripts:
Scripts used to benchmark the optmizers
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test_functions.py:
A module composed of mathematical functions for optmization tests
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example_parameters.py:
An example on how to build a parameters dictionary that must be passed to the optmizer
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/scripts/example_file_name.py.lprof:
Binary file contaning a line_profiler (detailed information on execution time per line) of the optmizer main function (for execution time improvement purposes)
- Marcelo Freitas - marcelofa
- Reginaldo Santos - initial sapso paper and implementation
- Abner Cardoso - initial studies on parallel sapso and implementation