Peter Jamieson
ABSTRACT
In this work, we introduce, GA-lapagos, an open-source genetic algorithm framework written in 'C' for 3 exemplar optimization problems, and an accompanying Python-based data analysis scripts to extract and produce results. We created this system to help researchers implement a fast GA solving system for their problems allowing them to implement and leverage many ideas implemented in the research literature. Additionally, we provide a number of compilation paths to parallel computational systems such as multi-core, GPUs, and FPGAs. By building an executable framework and outputting results in comma separated values (CSV) format, we create a set of Python scripts to read the data and create graphs.
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Index Terms
- GA-lapagos, an open-source c framework including a python-based system for data analysis
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