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Main Authors: Zhou, Aizhong, Wang, Fengbo, Guo, Jiong
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2405.05083
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author Zhou, Aizhong
Wang, Fengbo
Guo, Jiong
author_facet Zhou, Aizhong
Wang, Fengbo
Guo, Jiong
contents In many real-world applications of committee elections, the candidates are associated with certain attributes and the chosen committee is required to satisfy some constraints posed on the candidate attributes. For instance, when dress collocation, it is generally acknowledged that when wearing a tie, you'd better wear a shirt, and wearing a suit, you'd better wear leather shoes. Here, dresses are categorized by upper garment, lower garment, shoes et.al, and upper garment is with the attribute tie and shirt, lower garment is with the attribute suit, and shoes is with the attribute leather. And two constraints "tie infers shirt" and "suit infers leather shoes" are proposed. We study this variant of committee elections from the computational complexity viewpoint. Given a set of candidates, each with some attributes and a profit, and a set of constraints, given as propositional logical expressions of the attributes, the task is to compute a set of k candidates, whose attributes satisfy all constraints and whose total profit achieves a given bound. We achieve a dichotomy concerning classical complexity with no length limit on constraints: the problem is polynomial-time solvable, if the following two conditions are fulfilled: 1) each candidate has only one attribute and 2) each attribute occurs at most once in the constraints. It becomes NP-hard if one of the two conditions is violated. Moreover, we examine its parameterized complexity. The parameterization with the number of constraints, the size of the committee, or the total profit bound as parameter leads to para-NP-hardness or W[1]-hardness, while with the number of attributes or the number of candidates as parameter, the problem turns out to be fixed-parameter tractable.
format Preprint
id arxiv_https___arxiv_org_abs_2405_05083
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Committee Elections with Candidate Attribute Constraints
Zhou, Aizhong
Wang, Fengbo
Guo, Jiong
Computational Complexity
Computer Science and Game Theory
In many real-world applications of committee elections, the candidates are associated with certain attributes and the chosen committee is required to satisfy some constraints posed on the candidate attributes. For instance, when dress collocation, it is generally acknowledged that when wearing a tie, you'd better wear a shirt, and wearing a suit, you'd better wear leather shoes. Here, dresses are categorized by upper garment, lower garment, shoes et.al, and upper garment is with the attribute tie and shirt, lower garment is with the attribute suit, and shoes is with the attribute leather. And two constraints "tie infers shirt" and "suit infers leather shoes" are proposed. We study this variant of committee elections from the computational complexity viewpoint. Given a set of candidates, each with some attributes and a profit, and a set of constraints, given as propositional logical expressions of the attributes, the task is to compute a set of k candidates, whose attributes satisfy all constraints and whose total profit achieves a given bound. We achieve a dichotomy concerning classical complexity with no length limit on constraints: the problem is polynomial-time solvable, if the following two conditions are fulfilled: 1) each candidate has only one attribute and 2) each attribute occurs at most once in the constraints. It becomes NP-hard if one of the two conditions is violated. Moreover, we examine its parameterized complexity. The parameterization with the number of constraints, the size of the committee, or the total profit bound as parameter leads to para-NP-hardness or W[1]-hardness, while with the number of attributes or the number of candidates as parameter, the problem turns out to be fixed-parameter tractable.
title Committee Elections with Candidate Attribute Constraints
topic Computational Complexity
Computer Science and Game Theory
url https://arxiv.org/abs/2405.05083