Scheduling under Uncertainty

不确定性下的调度

• 批准号: 2599029
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2599029
• 关键词: Scheduling; under; Uncertainty

The well-known approaches in decision making under uncertainty are Stochastic Programming, Robust Optimisation and Stability Analysis. In spite of their long history of study and advanced theoretical findings, the practical applicability of the existing methods is often quite limited. The new methodology of Resiliency Analysis overcomes some of the drawbacks of the existing methods: it does not rely on probabilistic characteristics of uncertain parameters, on worst-case scenarios or optimality requirements of target solutions. The preliminary study of the classical Combinatorial Optimisation problems has indicated the benefits of Resiliency Analysis, which can provide not only theoretically rigorous, but also practically feasible methods for decision making under uncertainty. The project will elaborate the key methods of Resiliency Analysis further and apply them to important scheduling problems which have been under study for more than 60 years: single- and parallel-machine problems, open-shop, flow-shop and job-shop. Using the links between Scheduling Theory and other disciplines of Combinatorial Optimisation, we will make steps towards extending our study, considering such problems as optimisation on graphs and the assignment problem.

在不确定条件下进行决策的常用方法有随机规划、鲁棒优化和稳定性分析。尽管已有的方法有着悠久的研究历史和先进的理论成果，但它们的实际适用性往往很有限。弹性分析的新方法克服了现有方法的一些缺点：它不依赖于不确定参数的概率特征，不依赖于目标解的最坏情况或最优性要求。对经典组合优化问题的初步研究表明，弹性分析不仅可以为不确定条件下的决策提供理论严谨且实际可行的方法。该项目将进一步阐述弹性分析的关键方法，并将其应用于60多年来一直在研究的重要调度问题：单机和并行机问题、开放式车间、流水车间和作业车间。利用调度理论和其他组合优化学科之间的联系，我们将逐步扩展我们的研究，考虑诸如图上的优化和分配问题等问题。