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Constrained Task Assignment and Scheduling On Networks of Arbitrary Topology.

机译:任意拓扑网络上的受限任务分配和调度。

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摘要

This dissertation develops a framework to address centralized and distributed constrained task assignment and task scheduling problems. This framework is used to prove properties of these problems that can be exploited, develop effective solution algorithms, and to prove important properties such as correctness, completeness and optimality.;The centralized task assignment and task scheduling problem treated here is expressed as a vehicle routing problem with the goal of optimizing mission time subject to mission constraints on task precedence and agent capability. The algorithm developed to solve this problem is able to coordinate vehicle (agent) timing for task completion. This class of problems is NP-hard and analytical guarantees on solution quality are often unavailable. This dissertation develops a technique for determining solution quality that can be used on a large class of problems and does not rely on traditional analytical guarantees.;For distributed problems several agents must communicate to collectively solve a distributed task assignment and task scheduling problem. The distributed task assignment and task scheduling algorithms developed here allow for the optimization of constrained military missions in situations where the communication network may be incomplete and only locally known. Two problems are developed. The distributed task assignment problem incorporates communication constraints that must be satisfied; this is the Communication-Constrained Distributed Assignment Problem. A novel distributed assignment algorithm, the Stochastic Bidding Algorithm, solves this problem. The algorithm is correct, probabilistically complete, and has linear average-case time complexity.;The distributed task scheduling problem addressed here is to minimize mission time subject to arbitrary predicate mission constraints; this is the Minimum-time Arbitrarily-constrained Distributed Scheduling Problem. The Optimal Distributed Non-sequential Backtracking Algorithm solves this problem. The algorithm is correct, complete, outputs time optimal schedules, and has low average-case time complexity.;Separation of the task assignment and task scheduling problems is exploited here to ameliorate the effects of an incomplete communication network. The mission-modeling conditions that allow this and the benefits gained are discussed in detail. It is shown that the distributed task assignment and task scheduling algorithms developed here can operate concurrently and maintain their correctness, completeness, and optimality properties.
机译:本文开发了一个框架来解决集中式和分布式约束任务分配和任务调度问题。该框架用于证明可被利用的这些问题的性质,开发有效的解决方案算法,并证明诸如正确性,完整性和最优性之类的重要性质。此处处理的集中式任务分配和任务调度问题表示为车辆路线优化任务时间的目标受到任务优先级和代理能力的任务约束的影响。为解决此问题而开发的算法能够协调车辆(代理)的计时以完成任务。这类问题是NP难题,解决方案质量的分析保证通常不可用。本文提出了一种解决方案质量的确定技术,该技术可用于一类大的问题,而又不依赖于传统的分析保证。对于分布式问题,几个Agent必须进行沟通以共同解决分布式任务分配和任务调度问题。这里开发的分布式任务分配和任务调度算法允许在通信网络可能不完整且仅在本地已知的情况下优化受约束的军事任务。发展了两个问题。分布式任务分配问题包含了必须满足的通信约束。这是通信受限的分布式分配问题。一种新颖的分布式分配算法,随机投标算法,解决了这个问题。该算法是正确的,概率上完整的,并且具有线性的平均情况时间复杂度。此处解决的分布式任务调度问题是在受到任意谓词任务约束的情况下最小化任务时间;这是最小时间任意约束分布式调度问题。最优分布式非顺序回溯算法解决了这个问题。该算法是正确,完整,输出时间最优的调度表,并且平均情况下的时间复杂度较低。;本文利用任务分配和任务调度问题的分离来改善通信网络不完整的影响。详细讨论了允许这样做的任务建模条件以及所获得的收益。结果表明,本文开发的分布式任务分配和任务调度算法可以同时运行,并保持其正确性,完整性和最优性。

著录项

  • 作者

    Jackson, Justin Patrick.;

  • 作者单位

    University of Michigan.;

  • 授予单位 University of Michigan.;
  • 学科 Engineering Aerospace.;Engineering System Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 190 p.
  • 总页数 190
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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