Split Algorithm in Linear Time for the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Time Windows

TL;DR

This paper introduces a linear-time Split algorithm extension for complex vehicle routing problems, including pickup and delivery with time windows, improving efficiency while maintaining optimality under certain conditions.

Contribution

The authors extend the linear Split algorithm to handle VRPSPD and VRPTW variants, achieving optimal solutions in linear time and incorporating capacity penalties.

Findings

The extended algorithm runs in linear time, outperforming quadratic counterparts.

It guarantees optimality under the triangle inequality condition.

Empirical results confirm significant speed improvements.

Abstract

For many kinds of vehicle routing problems (VRPs), a popular heuristic approach involves constructing a Traveling Salesman Problem (TSP) solution, referred to as a long tour, then partitioning segments of the solution into routes for different vehicles with respect to problem constraints. Previously, a Split algorithm with a worst-case runtime of $\Theta(n)$ was proposed for the capacitated VRP (CVRP) that finds the most cost-efficient partition of customers, given a long tour. This was an improvement over the previously fastest-known Split algorithm with a worst-case runtime of $\Theta(n^2)$ that was based on Bellman's shortest path algorithm. While this linear Split has been an integral part of modern state-of-the-art CVRP approaches, little progress has been made in extending this algorithm to handle additional VRP variants, limiting the general applicability of the algorithm. In this work, we propose an extension of the linear Split that handles two cardinal VRP variants simultaneously: (i) simultaneous pickups and deliveries (VRPSPD) and (ii) time windows (VRPTW). The resulting $\Theta(n)$ algorithm is guaranteed to be optimal, assuming travel times between nodes satisfy the triangle inequality. Additionally, we extend the linear Split to handle a capacity penalty for the VRPSPD. For the VRPTW, we extend the linear Split to handle the CVRP capacity penalty in conjunction with the popular time warp penalty function. Computational experiments are performed to empirically validate the speed gains of these linear Splits against their $\Theta$($n^2$) counterparts.