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Fair and Efficient Cake Division with Connected Pieces

Arunachaleswaran, ER and Barman, S and Kumar, R and Rathi, N (2019) Fair and Efficient Cake Division with Connected Pieces. In: 15th Conference on Web and Internet Economics, WINE 2019, 10 - 12 December 2019, New York City, pp. 57-70.

Full text not available from this repository.
Official URL: https://doi.org/10.1007/978-3-030-35389-6_5

Abstract

The classic cake-cutting problem provides a model for addressing fair and efficient allocation of a divisible, heterogeneous resource (metaphorically, the cake) among agents with distinct preferences. Focusing on a standard formulation of cake cutting, in which each agent must receive a contiguous piece of the cake, this work establishes algorithmic and hardness results for multiple fairness/efficiency measures. First, we consider the well-studied notion of envy-freeness and develop an efficient algorithm that finds a cake division (with connected pieces) wherein the envy is multiplicatively within a factor of 3+o(1). The same algorithm in fact achieves an approximation ratio of 3+o(1) for the problem of finding cake divisions with as large a Nash social welfare (NSW) as possible. NSW is another standard measure of fairness and this work also establishes a connection between envy-freeness and NSW: approximately envy-free cake divisions (with connected pieces) always have near-optimal Nash social welfare. Furthermore, we develop an approximation algorithm for maximizing the ρ-mean welfare–this unifying objective, with different values of ρ, interpolates between notions of fairness (NSW) and efficiency (average social welfare). Finally, we complement these algorithmic results by proving that maximizing NSW (and, in general, the ρ-mean welfare) is APX-hard in the cake-division context.

Item Type: Conference Paper
Publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher: Springer
Additional Information: The copyright for this article belongs to the Authors.
Keywords: Artificial intelligence; Computer science; Computers, Approximation ratios; Cake cuttings; Efficient allocations; Envy-freeness; Fair divisions; Hardness result; Heterogeneous resources; Social welfare, Approximation algorithms
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 25 Oct 2022 10:32
Last Modified: 25 Oct 2022 10:32
URI: https://eprints.iisc.ac.in/id/eprint/77564

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