用JECoLi实现元启发式优化算法

Pedro Evangelista, Paulo Maia, Miguel Rocha
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引用次数: 16

摘要

这项工作提出了JECoLi -一个新颖的基于java的库,用于实现基于遗传和进化计算的元启发式优化算法。该库是基于灵活性、可用性、适应性、模块化、可扩展性、透明性、可扩展性、鲁棒性和计算效率的原则开发的。这个项目是开源的,所以JECoLi是在GPL许可下提供的,连同大量的文档和示例,都包含在一个基于wiki的社区网站(http://darwin.di.uminho.pt/jecoli)中。JECoLi已经/正在几个研究项目中使用,这些项目有助于形成其发展,应用领域从生物信息学到数据挖掘和计算机网络优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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, 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.
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