The cost due to delay in services may be intrinsically different for various applications of vehicle routing such as medical emergencies, logistical operations, and ride-sharing. We study a fundamental generalization of the Traveling Salesman Problem, namely Lp TSP, where the objective is to minimize an aggregated measure of the delay in services, quantified by the Minkowski p-norm of the delay vector. We present efficient combinatorial and Linear Programming algorithms for approximating Lp TSP on general metrics. We provide several approximation algorithms for the Lp TSP problem, including 4.27 & 10.92-approximation algorithms for single & multi vehicle L2 TSP, called the Traveling Firefighter Problem. Among other contributions, we provide an 8-approximation and a 1.78 inapproximability for All-Norm TSP problem, addressing scenarios where one does not know the ideal cost function, or is seeking simultaneous approximation with respect to any cost function.
@article{arxiv.2208.04410,
title = {Multi Purpose Routing: New Perspectives and Approximation Algorithms},
author = {Majid Farhadi and Jai Moondra and Prasad Tetali and Alejandro Toriello},
journal= {arXiv preprint arXiv:2208.04410},
year = {2022}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2107.10454