Implementing Metaheuristic Optimization Algorithms with JECoLi

  • Authors:
  • Pedro Evangelista;Paulo Maia;Miguel Rocha

  • Affiliations:
  • -;-;-

  • Venue:
  • ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
  • Year:
  • 2009

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Abstract

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 open-source, 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.