路径问题多目标鲁棒变体的代数框架

Pub Date : 2020-06-12 DOI:10.3336/gm.55.1.12
R. Manger
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引用次数: 0

摘要

众所周知,图中各种类型的路径问题可以在一个共同的代数框架内一起处理。因此,每种类型都具有不同的“路径代数”特征,即同一抽象代数结构的不同实例。本文证明了通用的代数框架,虽然最初是针对传统的问题变量,但可以扩展到涵盖多目标和鲁棒变量。因此,本文主要关注的是构造和证明与这些更复杂的问题变体对应的新路径代数。所得到的代数公式的一个结果是,多目标或鲁棒问题实例可以通过设计在任意路径代数上工作的众所周知的通用算法来解决。用这种方法得到的解包含了帕累托意义上所有有效的路径。默认情况下,有效路径只是隐式地描述为目标函数值的向量。然而,本文表明,使用所涉及代数的稍微扩展版本,同样的路径也可以被明确地识别。此外,对于鲁棒问题实例,可以根据广义最小最大或最小最大后悔准则只选择一条“鲁棒最优”路径。
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An algebraic framework for multi-objective and robust variants of path problems
It is well known that various types of path problems in graphs can be treated together within a common algebraic framework. Thereby each type is characterized by a different “path algebra”, i.e., a different instance of the same abstract algebraic structure. This paper demonstrates that the common algebraic framework, although originally intended for conventional problem variants, can be extended to cover multiobjective and robust variants. Thus the paper is mainly concerned with constructing and justifying new path algebras that correspond to such more complex problem varieties. A consequence of the obtained algebraic formulation is that multi-objective or robust problem instances can be solved by well-known general algorithms designed to work over an arbitrary path algebra. The solutions obtained in this way comprise all paths that are efficient in the Pareto sense. The efficient paths are by default described only implicitly, as vectors of objective-function values. Still, it is shown in the paper that, with slightly extended versions of the involved algebras, the same paths can also be identified explicitly. Also, for robust problem instances it is possible to select only one “robustly optimal” path according to a generalized min-max or min-max regret criterion.
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