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Hierarchical decomposition heuristic for scheduling: Coordinated reasoning for decentralized and distributed decision-making problems

机译:调度的分层分解试探法:分散和分布式决策问题的协调推理

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摘要

This paper presents a new technique for decomposing and rationalizing large decision-making problems into a common and consistent framework. We call this the hierarchical decomposition heuristic (HDH) which focuses on obtaining "globally feasible" solutions to the overall problem, i.e., solutions which are feasible for all decision-making elements in a system. The HDH is primarily intended to be applied as a standalone tool for managing a decentralized and distributed system when only globally consistent solutions are necessary or as a lower bound to a maximization problem within a global optimization strategy such as Lagrangean decomposition. An industrial scale scheduling example is presented that demonstrates the abilities of the HDH as an iterative and integrated methodology in addition to three small motivating examples. Also illustrated is the HDH's ability to support several types of coordinated and collaborative interactions.
机译:本文提出了一种将大型决策问题分解和合理化为一个通用且一致的框架的新技术。我们称其为分层分解启发式(HDH),其重点是为整个问题获取“全局可行”的解决方案,即对系统中所有决策要素都可行的解决方案。当仅需要全局一致的解决方案时,HDH主要旨在用作管理分散和分布式系统的独立工具,或者用作全局优化策略(例如拉格朗日分解)中最大化问题的下限。提出了一个工业规模的调度示例,除了三个小的激励示例外,还演示了HDH作为迭代和集成方法的功能。还说明了HDH支持多种类型的协调和协作交互的能力。

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