Improved Approximation Algorithms for Capacitated Vehicle Routing with Fixed Capacity

Abstract: The Capacitated Vehicle Routing Problem (CVRP) is one of the most extensively studied problems in combinatorial optimization. According to the property of the demand of customers, we distinguish three variants of CVRP: unit-demand, splittable and unsplittable. We consider $k$-CVRP in general metrics and general graphs, where $k$ is the capacity of the vehicle and all the three versions are APX-hard for each fixed $k\geq 3$. In this paper, we give a $(5/2-\Theta(\sqrt{1/k}))$-approximation algorithm for splittable and unit-demand $k$-CVRP and a $(5/2+\ln2-\Theta(\sqrt{1/k}))$-approximation algorithm for unsplittable $k$-CVRP. Our approximation ratio is better than all previous results for $k$ smaller than a sufficiently large value, say $k\leq 1.7\times 10^7$. For small $k$, we also design independent elegant algorithms with further improvements. For the splittable and unit-demand cases, we improve the ratio from $1.792$ to $1.500$ for $k=3$, and from $1.750$ to $1.500$ for $k=4$ too. For the unsplittable case, we improve the ratio from $1.792$ to $1.500$ for $k=3$, from $2.051$ to $1.750$ for $k=4$, and from $2.249$ to $2.157$ for $k=5$. The approximation ratio for $k=3$ also surprisingly achieve the same ratio for the splittable case. Note that for small $k$ such as $3$, $4$ and $5$, some previous results have also been kept for decades. Our techniques, such as the EX-ITP method -- an extension of the classic ITP method, has potential to improve algorithms for more routing problems.