Parameterized Analysis of Bio-inspired Computing - From Theory to High Performing Algorithms

仿生计算的参数化分析——从理论到高性能算法

• 批准号: DP140103400
• 负责人: Prof Frank Neumann
• 金额: $ 20.97万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140103400
• 关键词: Parameterized; Analysis; Bio; inspired; Computing

This project will establish the field of parameterised analysis of bio-inspired computing which includes prominent approaches such as evolutionary algorithms and ant colony optimisation. It will rigorously analyse features of instances of combinatorial optimisation problems and their impact on the runtime behaviour of bio-inspired computing methods. Furthermore, the project will design new bio-inspired computing algorithms that make use of instance features and hardness characteristics. The results will advance the theoretical knowledge of bio-inspired computing, bridge the gap between theory and practice, and provide more powerful algorithms for complex optimisation problems occurring for example in the field of supply chain management for the mining industry.

该项目将建立生物启发计算的参数化分析领域，其中包括进化算法和蚁群优化等突出方法。它将严格分析组合优化问题实例的特征及其对生物启发计算方法运行时行为的影响。此外，该项目将设计新的生物启发计算算法，利用实例特征和硬度特征。研究结果将推进生物启发计算的理论知识，弥合理论与实践之间的差距，并为采矿业供应链管理等领域的复杂优化问题提供更强大的算法。