Contiguous Allocation of Indivisible Items on a Path

TL;DR

The paper investigates contiguous allocations of indivisible items on a path (CAP) under additive valuations, contrasting fixed-order and flexible-order regimes. It achieves polynomial-time algorithms for maximizing utilitarian and egalitarian welfare and related notions under fixed order via dynamic programming and constructive techniques, while establishing NP-hardness for EF1 in fixed order and for U-max and E-max in flexible order under sparsity. It also delivers approximation guarantees, notably a 2-approximation for the special binary-additive case with maximum utility $m$ and a $1/a$-approximation for $(a,b)$-sparse instances, plus several FPT algorithms parameterized by the number of agents or items. The results delineate a clear dichotomy: fixed-order CAP admits efficient computation for many objectives but not EF1, whereas flexible-order CAP is computationally intractable for core welfare objectives yet amenable to approximation and parameterized approaches in structured sparse settings. These insights advance the understanding of fair and efficient contiguous allocations and lay groundwork for future improvements in algorithms and hardness bounds.

Abstract

We study the problem of allocating indivisible items on a path among agents. The objective is to find a fair and efficient allocation in which each agent's bundle forms a contiguous block on the line. We say that an instance is \emph{$(a, b)$-sparse} if each agent values at most $a$ items positively and each item is valued positively by at most $b$ agents. We demonstrate that, even when the valuations are binary additive, deciding whether every item can be allocated to an agent who wants it is NP-complete for the $(4,3)$-sparse instances. Consequently, we provide two fixed-parameter tractable (FPT) algorithms for maximizing utilitarian social welfare, with respect to the number of agents and the number of items. Additionally, we present a $2$-approximation algorithm for the special case when the valuations are binary additive, and the maximum utility is equal to the number of items. Also, we provide a $1/a$-approximation algorithm for the $(a,b)$-sparse instances. Furthermore, we establish that deciding whether the maximum egalitarian social welfare is at least $2$ or at most $1$ is NP-complete for the $(6,3)$-sparse instances, even when the valuations are binary additive. We present a $1/a$-approximation algorithm for maximizing egalitarian social welfare for the $(a,b)$-sparse instances. Besides, we give two FPT algorithms for maximizing egalitarian social welfare in terms of the number of agents and the number of items. We also explore the case where the order of the blocks of items allocated to the agents is predetermined. In this case, we show that both maximum utilitarian social welfare and egalitarian social welfare can be computed in polynomial time. However, we determine that checking the existence of an EF1 allocation is NP-complete, even when the valuations are binary additive.

Figures (1)

• Figure 1: The valuation of the agents in Example \ref{['ex:fixed-order']}

Theorems & Definitions (26)

• Example 1
• Theorem 1
• Corollary 1
• proof
• Theorem 2
• Theorem 3
• Corollary 2
• Theorem 4
• Theorem 5
• Theorem 6