Approximation Algorithms for Drone Delivery Scheduling Problem

TL;DR

This paper introduces approximation algorithms for optimizing drone delivery schedules, focusing on maximizing profit while respecting battery constraints, including a fully polynomial scheme for single drones and a 1/4-approximation for multiple drones.

Contribution

It presents the first FPTAS for the single drone scheduling problem and a novel approximation algorithm for the multi-drone delivery scheduling problem under drone number constraints.

Findings

FPTAS achieves near-optimal solutions for SDSP.

1/4-approximation algorithm provides guaranteed performance for MDSP.

Algorithms are polynomial-time and applicable to real-world drone delivery scenarios.

Abstract

The coordination among drones and ground vehicles for last-mile delivery has gained significant interest in recent years. In this paper, we study \textit{multiple drone delivery scheduling problem(MDSP) \cite{Betti_ICDCN22} for last-mile delivery, where we have a set of drones with an identical battery budget and a set of delivery locations, along with reward or profit for delivery, cost and delivery time intervals. The objective of the MDSP is to find a collection of conflict-free schedules for each drone such that the total profit for delivery is maximum subject to the battery constraint of the drones. Here we propose a fully polynomial time approximation scheme (FPTAS) for the single drone delivery scheduling problem (SDSP) and a $\frac{1}{4}$-approximation algorithm for MDSP with a constraint on the number of drones.