Implementing metaheuristic optimization algorithms with JECoLi

This work proposes JECoLi - a novel Java-based library for the implementation of metaheuristic optimization algorithms with a focus on Genetic and Evolutionary Computation based methods. The library was developed based on the principles of flexibility, usability, adaptability, modularity, extensibil...

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Detalhes bibliográficos
Autor principal: Evangelista, Pedro (author)
Outros Autores: Maia, Paulo (author), Rocha, Miguel (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2009
Assuntos:
Texto completo:http://hdl.handle.net/1822/16868
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/16868
Descrição
Resumo:This work proposes JECoLi - a novel Java-based library for the implementation of metaheuristic optimization algorithms with a focus on Genetic and Evolutionary Computation based methods. The library was developed based on the principles of flexibility, usability, adaptability, modularity, extensibility, transparency, scalability, robustness and computational efficiency. The project is opensource, so JECoLi is made available under the GPL license, together with extensive documentation and examples, all included in a community Wiki-based web site (http://darwin.di.uminho.pt/jecoli). JECoLi has been/is being used in several research projects that helped to shape its evolution, ranging application fields from Bioinformatics, to Data Mining and Computer Network optimization.