Evolutionary multi-objective algorithms for Global Grids

全球网格的进化多目标算法

• 批准号: DP0664674
• 负责人: Prof Michael Kirley
• 金额: $ 8.6万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2006
• 资助国家: 澳大利亚
• 起止时间: 2006-01-01 至 2009-03-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0664674
• 关键词: Evolutionary; multi; objective; algorithms; Global

This research investigates alternative software technologies for Grid-based evolutionary multi-objective decision algorithms. By employing the latest adaptive techniques and taking advantage of the low cost Grid infrastructure, new parallel evolutionary systems will be developed that can rapidly supply robust solutions to complex problems. This project will further develop an understanding of scaling issues in parallel evolutionary systems and pave the way for even more widespread application of evolutionary techniques for large scale, data-intensive applications in science and industry.

本研究探讨了基于网格的进化多目标决策算法的替代软件技术。通过采用最新的自适应技术，并利用低成本的网格基础设施，新的并行进化系统将开发，可以快速提供强大的解决方案，复杂的问题。 该项目将进一步发展对并行进化系统中的缩放问题的理解，并为进化技术在科学和工业中的大规模数据密集型应用的更广泛应用铺平道路。