Towards reliability in combinatorial optimisation

实现组合优化的可靠性

• 批准号: DE160100568
• 负责人: Dr Graeme Gange
• 金额: $ 25.22万
• 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: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-04-01 至 2021-12-03
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE160100568
• 关键词: Towards; reliability; combinatorial; optimisation

This project intends to develop techniques to ensure that the solutions reported by optimisation tools are correct and verifiable. Combinatorial optimisation problems, where the best solution must be found from a vast set of possibilities, are central to critical sectors of the economy, including shipping, transit, mining and emergency response. Automated tools for these problems can now solve large industrial examples, however, they are incredibly complex artefacts which are prone to error and difficult to test. New methods for ensuring the correctness of automated tools would allow users to trust that the results returned by these tools are correct when making critical decisions.

该项目旨在开发技术，以确保优化工具报告的解决方案是正确和可验证的。组合优化问题，必须从大量的可能性中找到最佳解决方案，是关键经济部门的核心，包括航运，运输，采矿和应急响应。针对这些问题的自动化工具现在可以解决大型工业实例，然而，它们是非常复杂的人工制品，容易出错并且难以测试。确保自动化工具正确性的新方法将允许用户在做出关键决策时相信这些工具返回的结果是正确的。