Capacitated Vehicle Routing in Graphic Metrics

TL;DR

This paper introduces a new tight lower bound for the capacitated vehicle routing problem in graphic metrics, leading to improved approximation algorithms with a ratio of 1.95, enhancing solution quality for this specific metric class.

Contribution

The paper presents a simple, combinatorial, and tight lower bound for graphic CVRP, and analyzes the approximation ratio of classical algorithms using this bound.

Findings

New tight lower bound for graphic CVRP

Approximation ratio improved to 1.95 for graphic CVRP

Analysis of classical algorithms with the new bound

Abstract

We study the capacitated vehicle routing problem in graphic metrics (graphic CVRP). Our main contribution is a new lower bound on the cost of an optimal solution. For graphic metrics, this lower bound is tight and significantly stronger than the well-known bound for general metrics. The proof of the new lower bound is simple and combinatorial. Using this lower bound, we analyze the approximation ratio of the classical iterated tour partitioning algorithm combined with the TSP algorithms for graphic metrics of Christofides [1976], of M\"omke-Svensson [JACM 2016], and of Seb\H{o}-Vygen [Combinatorica 2014]. In particular, we obtain a 1.95-approximation for the graphic CVRP.