A Java-Based Distributed Genetic Algorithm Framework
A Java-Based Distributed Genetic Algorithm Framework
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DOI：
10.1109/ictai.2007.17
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发表时间：
2007-10
期刊：
影响因子：
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通讯作者：
Gabi Escuela;Yudith Cardinale;Jorge González
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文献类型：
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作者：
Gabi Escuela;Yudith Cardinale;Jorge González
分布式遗传算法是最有前途的优化方法之一。在本文中，我们描述DGAFrame，阿尔法灵活的进化计算框架，用Java编写的。DGAFrame在通过RMI网络技术通信的一系列机器上执行GA，允许使用岛模型方法实现可移植的、灵活的GA。每个岛都可以独立于其他岛进行配置，从而实现异构DGA。为了评估DGAFrame的性能，我们实现了蛋白质结构预测问题，并通过解决方案的质量将DGA执行与其顺序执行进行比较。我们还测量了计算通信比，结果表明，建议始终优于等效的顺序遗传算法。
Distributed genetic algorithm (DGA) is one of the most promising choices among the optimization methods. In this paper we describe DGAFrame, alpha flexible framework for evolutionary computation, written in Java. DGAFrame executes GAs across a range of machines communicating through RMI network technology, allowing the implementation of portable, flexible GAs that use the island model approach. Each island can be configured independently from others providing the implementation of heterogeneous DGAs. To evaluate the performance of DGAFrame, we implemented the protein structure prediction problem and compare the DGA execution to its sequential counterpart through quality of solution. We also measure the computation to communication ratio and results show that the proposals consistently outperform equivalent sequential GAs.