Adaptive Optimisation of Complex Combinatorial Problems

复杂组合问题的自适应优化

• 批准号: DE140100017
• 负责人: A/Prof Aldeida Aleti
• 金额: $ 27.6万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-12 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE140100017
• 关键词: Adaptive; Optimisation; Complex; Combinatorial; Problems

One of the most common problems faced by planners, whether in industry or government, is optimisation, finding the optimal solution to a problem. Even a one per cent improvement in a solution can make a difference of millions of dollars in some cases. Traditionally optimisation problems are solved by analytic means or exact optimisation methods. Today, however, many optimisation problems involve complex combinatorial systems that make such traditional approaches unsuitable or intractable. This project aims to assist researchers and practitioners in solving complex combinatorial optimisation problems by adapting the optimisation strategy to the problem being solved, based on problem features such as search space difficulty.

无论是在行业还是政府，规划者面临的最常见问题之一是优化，即找到问题的最佳解决方案。在某些情况下，即使解决方案有1%的改进，也可以产生数百万美元的差异。传统上，优化问题是通过解析方法或精确优化方法来解决的。然而，今天，许多优化问题涉及复杂的组合系统，使得这种传统方法不适合或难以处理。该项目旨在帮助研究人员和实践者解决复杂的组合优化问题，方法是根据搜索空间困难等问题特征，使优化策略适应所解决的问题。