DocumentCode
2843745
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
fYear
2009
fDate
Nov. 30 2009-Dec. 2 2009
Firstpage
505
Lastpage
510
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ISDA.2009.161
Filename
5364947
Link To Document