The SBP Algorithm for Maximizing Revenue in Online Dial-a-Ride

December 13, 2019 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Ananya Christman, Christine Chung, Nicholas Jaczko, Tianzhi Li, Scott Westvold, Xinyue Xu arXiv ID 1912.06300 Category cs.DS: Data Structures & Algorithms Citations 0 Venue arXiv.org Last Checked 5 months ago
Abstract
In the Online-Dial-a-Ride Problem (OLDARP) a server travels through a metric space to serve requests for rides. We consider a variant where each request specifies a source, destination, release time, and revenue that is earned for serving the request. The goal is to maximize the total revenue earned within a given time limit. We prove that no non-preemptive deterministic online algorithm for OLDARP can be guaranteed to earn more than twice the revenue earned by an optimal offline solution. We then investigate the \textsc{segmented best path} ($SBP$) algorithm of~\cite{atmos17} for the general case of weighted graphs. The previously-established lower and upper bounds for the competitive ratio of $SBP$ are 4 and 6, respectively, under reasonable assumptions about the input instance. We eliminate the gap by proving that the competitive ratio is 5 (under the same reasonable assumptions). We also prove that when revenues are uniform, $SBP$ has competitive ratio 4. Finally, we provide a competitive analysis of $SBP$ on complete bipartite graphs.
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