Computing the Center of Uncertain Points on Cactus Graphs

TL;DR

This paper introduces an efficient algorithm for finding the optimal center point on a cactus graph that minimizes the maximum expected distance to uncertain points with probabilistic locations.

Contribution

It presents the first known algorithm for the weighted one-center problem on cactus graphs with near-optimal time complexity.

Findings

Algorithm runs in O(|G| + mn log mn) time

Solution is nearly optimal given input size

Addresses a previously unsolved problem in graph optimization

Abstract

In this paper, we consider the (weighted) one-center problem of uncertain points on a cactus graph. Given are a cactus graph $G$ and a set of $n$ uncertain points. Each uncertain point has $m$ possible locations on $G$ with probabilities and a non-negative weight. The (weighted) one-center problem aims to compute a point (the center) $x^*$ on $G$ to minimize the maximum (weighted) expected distance from $x^*$ to all uncertain points. No previous algorithm is known for this problem. In this paper, we propose an $O(|G| + mn\log mn)$-time algorithm for solving it. Since the input is $O(|G|+mn)$, our algorithm is almost optimal.