Bio-inspired Computing for Problems with Chance Constraints

针对机会约束问题的仿生计算

• 批准号: FT200100536
• 负责人: Prof Frank Neumann
• 金额: $ 73.21万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-06-30 至 2025-06-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT200100536
• 关键词: Bio; inspired; Computing; Problems; Chance

Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high performing bio-inspired algorithms for stochastic problems where the constraints can only be violated with a small probability. The outcomes will lead to more effective and reliable optimisation methods for complex planning processes in areas of national priority such as mining and manufacturing.

生物启发算法已成功应用于广泛的优化问题。在现实世界的应用中，不稳定可能导致生产计划或安全关键系统的严重故障。机会约束模型的不确定性，并允许限制这种故障的可能性。这个未来的奖学金建立了生物启发计算的机会约束问题的领域。 它为随机问题开发了高性能的生物启发算法，其中约束只能以很小的概率被违反。这些成果将为采矿和制造业等国家优先领域的复杂规划过程带来更有效和可靠的优化方法。