GTAIDSMar 23, 2021

Facility Reallocation on the Line

arXiv:2103.12894v11 citations
Originality Incremental advance
AI Analysis

This addresses facility location optimization for agents over time, with incremental contributions to algorithmic game theory.

The paper tackles the problem of multi-stage facility reallocation on a line to minimize social cost, including movement costs, and derives optimal algorithms for offline and online settings, with a competitive ratio of (n+2)/(n+1) for the online case and proposes a strategy-proof mechanism with ratios up to (n+4)/n.

We consider a multi-stage facility reallocation problems on the real line, where a facility is being moved between time stages based on the locations reported by $n$ agents. The aim of the reallocation algorithm is to minimise the social cost, i.e., the sum over the total distance between the facility and all agents at all stages, plus the cost incurred for moving the facility. We study this problem both in the offline setting and online setting. In the offline case the algorithm has full knowledge of the agent locations in all future stages, and in the online setting the algorithm does not know these future locations and must decide the location of the facility on a stage-per-stage basis. We derive the optimal algorithm in both cases. For the online setting we show that its competitive ratio is $(n+2)/(n+1)$. As neither of these algorithms turns out to yield a strategy-proof mechanism, we propose another strategy-proof mechanism which has a competitive ratio of $(n+3)/(n+1)$ for odd $n$ and $(n+4)/n$ for even $n$, which we conjecture to be the best possible. We also consider a generalisation with multiple facilities and weighted agents, for which we show that the optimum can be computed in polynomial time for a fixed number of facilities.

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