Optimized Scheduling of Complex Resource Allocation Systems through Approximate Dynamic Programming

这笔赠款为开发管理当代生产和服务系统中发生的复杂资源分配的新框架提供资金。该框架的定义特征是将在上述环境中遇到的总体资源分配问题分解成两个主要的子问题：第一个子问题被称为目标环境的逻辑或行为控制问题，它试图防止系统行为中出现有问题的或不期望的模式。解决这一子问题的方法论基础是由定性离散事件系统(DES)理论提供的一系列结果。第二个子问题称为性能控制或调度问题，它寻求在第一个子问题返回的逻辑控制器提供的行为范围内优化一些选定的性能指标。马尔可夫决策过程(MDP)理论和它的一些最新发展，统称为近似动态规划(ADP)，为第二个子问题提供了方法论基础。在拟议的调查中，特别强调了上述问题的典型基础是非常高的计算复杂性，所寻求的解决方案将寻求提供明确的杠杆，使系统设计者能够系统地权衡计算和操作效率。最后，通过将所提出的理论发展应用于(I)柔性自动化生产单元和(Ii)工业自动导引车(AGV)系统的产能最大化问题，所提出的理论发展将被具体化。如果成功，本研究的结果将使调度理论的现有发展更接近于现场实践，因为它们将有助于更有效地处理潜在的复杂性。通过这种方式，它们将实现并促进许多当代应用程序经常设想的并发性和操作灵活性，但在实践中受到限制，因为目前无法掌握这些概念产生的操作复杂性。在更具分析性的层面上，拟议的研究将进一步促进ADP的新兴领域，并将确定和追求这一领域与定性DES理论之间新的有趣的协同效应。最后，在教育方面，拟议的计划将促进和加强DES和ADP理论在工程学研究生课程中的存在，并将使一些研究生有机会通过积极参与所追求的研究来体验这些理论及其结果的潜力。

This grant provides funding for the development of a novel framework for managing the complex resource allocation that takes place in contemporary production and service systems. A defining characteristic of this framework is the decomposition of the overall resource allocation problem encountered in the aforementioned environments into two major sub-problems: The first of these sub-problems is known as the Logical or Behavioral Control problem for the target environments, and it seeks to prevent the development of problematic or undesirable patterns in the system behavior. The methodological base for addressing this sub-problem is a body of results provided by Qualitative Discrete Event Systems (DES) theory. The second sub-problem is known as the Performance Control or Scheduling problem, and it seeks to optimize some chosen performance indices within the behavioral latitude provided by the logical controller that is returned by the first sub-problem. The methodological base for this second sub-problem is provided by the theory of Markov Decision Processes (MDP) and some more recent developments in it, collectively known as Approximate Dynamic Programming (ADP). In the proposed investigations, special emphasis is placed on the very high computational complexity that typically underlies the aforementioned problems, and the pursued solutions will seek to provide explicit levers that will enable the system designers to systematically trade-off computational and operational efficiencies. Finally, the proposed theoretical developments will be concretized by applying them to the problems of throughput maximization of (i) flexibly automated production cells and (ii) industrial Automated Guided Vehicle (AGV) systems.If successful, the results of this research will bring closer the existing developments in scheduling theory to the field practice, since they will help to deal more effectively with the underlying complexities. In this way, they will enable and promote the concurrency and the operational flexibilities that have been frequently envisioned for many contemporary applications, but have been limited in practice by the current inability to master the operational complexity that stems from these concepts. At a more analytical level, the proposed research will further promote the burgeoning area of ADP and it will identify and pursue new interesting synergies between this area and Qualitative DES theory. Finally, on the educational side, the proposed program will promote and strengthen the presence of the DES and ADP theories in the graduate engineering curriculum, and it will give the opportunity to a number of graduate students to experience the potential of these theories and their results, through active participation in the pursued research.