Title :
Implementing Metaheuristic Optimization Algorithms with JECoLi
Author :
Evangelista, Pedro ; Maia, Paulo ; Rocha, Miguel
Author_Institution :
CCTC-Comput. Sci. & Technol. Center, Univ. do Minho, Braga, Portugal
fDate :
Nov. 30 2009-Dec. 2 2009
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.
Keywords :
Java; genetic algorithms; public domain software; software portability; GPL license; JECoLi; Java-based library; adaptability; computational efficiency; evolutionary computation; extensibility; flexibility; genetic computation; metaheuristic optimization algorithm; modularity; open-source project; robustness; scalability; transparency; usability; Computational efficiency; Evolutionary computation; Genetics; Java; Libraries; Open source software; Optimization methods; Robustness; Scalability; Usability; Evolutionary Computation; Java; Metaheuristics; Open-source software;
Conference_Titel :
Intelligent Systems Design and Applications, 2009. ISDA '09. Ninth International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-4735-0
Electronic_ISBN :
978-0-7695-3872-3
DOI :
10.1109/ISDA.2009.161