Verification of Multi-Layered Assignment Problems
Barak Steindl, Meirav Zehavi

TL;DR
This paper explores the complexity of verifying multi-layered assignment problems where agents have multiple incomplete preferences, introducing new verification notions and analyzing their computational complexity under various parameters.
Contribution
It generalizes verification problems to multi-layered preferences and provides a detailed parameterized complexity analysis for these new notions.
Findings
Three new multi-layer verification problems introduced
Complexity results characterized for various parameters
Most problems are computationally hard under common parameters
Abstract
The class of assignment problems is a fundamental and well-studied class in the intersection of Social Choice, Computational Economics and Discrete Allocation. In a general assignment problem, a group of agents expresses preferences over a set of items, and the task is to allocate items to agents in an "optimal" way. A verification variant of this problem includes an allocation as part of the input, and the question becomes whether this allocation is "optimal". In this paper, we generalize the verification variant to the setting where each agent is equipped with multiple incomplete preference lists: Each list (called a layer) is a ranking of items in a possibly different way according to a different criterion. In particular, we introduce three multi-layer verification problems, each corresponds to an optimality notion that weakens the notion of global optimality (that is, pareto…
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