2019Unpublished venueOpen access

Uncertainty Intervals for Robust Bottleneck Assignment

Michael Elad, Tony A. Wood, Chris Manzie, Iman Shames

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Abstract

We examine the robustness of bottleneck assignment problems to perturbations in the assignment weights. We derive two algorithms that provide uncertainty bounds for robust assignment. We prove that the bottleneck assignment is guaranteed to be invariant to perturbations which lie within the provided bounds. We apply the method to an example of task assignment for a multi-agent system.

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What this paper is about

We examine the robustness of bottleneck assignment problems to perturbations in the assignment weights. We derive two algorithms that provide uncertainty bounds for robust assignment. We prove that the bottleneck assignment is guaranteed to be invariant to perturbations which lie within the provided bounds. We apply the method to an example of task assignment for a multi-agent system.

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Available abstract

We examine the robustness of bottleneck assignment problems to perturbations in the assignment weights. We derive two algorithms that provide uncertainty bounds for robust assignment. We prove that the bottleneck assignment is guaranteed to be invariant to perturbations which lie within the provided bounds. We apply the method to an example of task assignment for a multi-agent system.

Key concepts: Bottleneck, Linear bottleneck assignment problem, Robustness (evolution), Weapon target assignment problem, Assignment problem, Generalized assignment problem, Computer science, Mathematical optimization

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