Welfare bounds in the fair division problem

1991 ◽  
Vol 54 (2) ◽  
pp. 321-337 ◽  
Author(s):  
Hervé Moulin
1964 ◽  
Vol 37 (5) ◽  
pp. 341-342 ◽  
Author(s):  
A. M. Fink

Author(s):  
Arpita Biswas ◽  
Siddharth Barman

We consider the problem of fairly allocating indivisible goods, among agents, under cardinality constraints and additive valuations. In this setting, we are given a partition of the entire set of goods---i.e., the goods are categorized---and a limit is specified on the number of goods that can be allocated from each category to any agent. The objective here is to find a fair allocation in which the subset of goods assigned to any agent satisfies the given cardinality constraints. This problem naturally captures a number of resource-allocation applications, and is a generalization of the well-studied unconstrained fair division problem.  The two central notions of fairness, in the context of fair division of indivisible goods, are envy freeness up to one good (EF1) and the (approximate) maximin share guarantee (MMS). We show that the existence and algorithmic guarantees established for these solution concepts in the unconstrained setting can essentially be achieved under cardinality constraints. Furthermore, focusing on the case wherein all the agents have the same additive valuation, we establish that EF1 allocations exist even under matroid constraints.


1964 ◽  
Vol 37 (5) ◽  
pp. 341 ◽  
Author(s):  
A. M. Fink

2000 ◽  
Vol 68 (3) ◽  
pp. 299-302 ◽  
Author(s):  
François Maniquet ◽  
Yves Sprumont

2013 ◽  
Vol 14 (1) ◽  
pp. 11-27
Author(s):  
William Olvera-López ◽  
Francisco Sánchez-Sánchez

Author(s):  
Bo Li ◽  
Wenyang Li ◽  
Yingkai Li

In this paper, we focus on how to dynamically allocate a divisible resource fairly among n players who arrive and depart over time. The players may have general heterogeneous valuations over the resource. It is known that the exact envy-free and proportional allocations may not exist in the dynamic setting [Walsh, 2011]. Thus, we will study to what extent we can guarantee the fairness in the dynamic setting. We first design two algorithms which are O(log n)-proportional and O(n)-envy-free for the setting with general valuations, and by constructing the adversary instances such that all dynamic algorithms must be at least Omega(1)-proportional and Omega(n/log n)-envy-free, we show that the bounds are tight up to a logarithmic factor. Moreover, we introduce the setting where the players' valuations are uniform on the resource but with different demands, which generalize the setting of [Friedman et al., 2015]. We prove an O(log n) upper bound and a tight lower bound for this case. 


Author(s):  
Argyrios Deligkas ◽  
Eduard Eiben ◽  
Robert Ganian ◽  
Thekla Hamm ◽  
Sebastian Ordyniak

We study the Connected Fair Division problem (CFD), which generalizes the fundamental problem of fairly allocating resources to agents by requiring that the items allocated to each agent form a connected subgraph in a provided item graph G. We expand on previous results by providing a comprehensive complexity-theoretic understanding of CFD based on several new algorithms and lower bounds while taking into account several well-established notions of fairness: proportionality, envy-freeness, EF1 and EFX. In particular, we show that to achieve tractability, one needs to restrict both the agents and the item graph in a meaningful way. We design (XP)-algorithms for the problem parameterized by (1) clique-width of G plus the number of agents and (2) treewidth of G plus the number of agent types, along with corresponding lower bounds. Finally, we show that to achieve fixed-parameter tractability, one needs to not only use a more restrictive parameterization of G, but also include the maximum item valuation as an additional parameter.


Author(s):  
Julius B. Barbanel ◽  
Alan D. Taylor
Keyword(s):  

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