English

Multi Purpose Routing: New Perspectives and Approximation Algorithms

Data Structures and Algorithms 2022-08-10 v1

Abstract

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 LpL_p TSP, where the objective is to minimize an aggregated measure of the delay in services, quantified by the Minkowski pp-norm of the delay vector. We present efficient combinatorial and Linear Programming algorithms for approximating LpL_p TSP on general metrics. We provide several approximation algorithms for the LpL_p TSP problem, including 4.274.27 & 10.9210.92-approximation algorithms for single & multi vehicle L2L_2 TSP, called the Traveling Firefighter Problem. Among other contributions, we provide an 88-approximation and a 1.781.78 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.

Keywords

Cite

@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

R2 v1 2026-06-25T01:34:50.380Z