Design and implementation of a distributed evolutionary computing software

K. Tan, A. Tay, J. Cai
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引用次数: 25

Abstract

Although evolutionary algorithm is a powerful optimization tool, its computation cost involved in terms of time and hardware resources increases as the size or complexity of the problem increases. One promising approach to overcome this limitation is to exploit the inherent parallelism of evolutionary algorithms by creating an infrastructure necessary to support distributed evolutionary computing using existing Internet and hardware resources. This paper presents a Java-based distributed evolutionary computing software (Paladin-DEC), which enhances the concurrent processing and performance of evolutionary algorithms by allowing inter-communications of subpopulations among various computers over the Internet. Such a distributed system enables individuals to migrate among multiple subpopulations according to some patterns to induce diversity of elite individuals periodically, in a way that simulates the species evolve in natural environment. The Paladin-DEC software is capable of keeping data integrity throughout the computation, and is incorporated with the features of robustness, security, fault tolerance, and work balancing. The effectiveness and advantages of the Paladin-DEC are illustrated upon two case studies of drug scheduling in cancer chemotherapy and searching probe sets of yeast genome.
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分布式进化计算软件的设计与实现
虽然进化算法是一种强大的优化工具,但随着问题的规模或复杂性的增加,它所涉及的计算成本在时间和硬件资源方面也会增加。克服这一限制的一种有希望的方法是利用进化算法固有的并行性,通过创建必要的基础设施来支持使用现有Internet和硬件资源的分布式进化计算。本文提出了一种基于java的分布式进化计算软件(Paladin-DEC),该软件通过允许Internet上不同计算机之间的子种群相互通信,提高了进化算法的并发处理和性能。这种分布式系统使个体能够按照一定的模式在多个亚种群之间迁移,从而周期性地诱导精英个体的多样性,从而模拟物种在自然环境中的进化。Paladin-DEC软件能够在整个计算过程中保持数据的完整性,并具有鲁棒性、安全性、容错性和工作平衡等特点。Paladin-DEC在肿瘤化疗药物调度和酵母基因组探针组搜索方面的两个案例说明了其有效性和优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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3 months
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