Arc Routing Problems with Multiple Trucks and Drones: A Hybrid Genetic Algorithm

TL;DR

This paper introduces a hybrid genetic algorithm for solving a complex arc routing problem involving multiple trucks and drones, aiming to minimize total service time in logistics operations.

Contribution

It presents a novel hybrid genetic algorithm tailored for the RPP-mTD, integrating specialized encoding, crossover, and local search techniques for large-scale, multi-vehicle routing.

Findings

The proposed HGA outperforms existing methods on benchmark instances.

Scalability is demonstrated on larger, more complex problem instances.

Operational benefits of integrated truck-drone fleets are validated.

Abstract

Arc-routing problems underpin numerous critical field operations, including power-line inspection, urban police patrolling, and traffic monitoring. In this domain, the Rural Postman Problem (RPP) is a fundamental variant in which a prescribed subset of edges or arcs in a network must be traversed. This paper investigates a generalized form of the RPP, called RPP-mTD, which involves a fleet of multiple trucks, each carrying multiple drones. The trucks act as mobile depots traversing a road network, from which drones are launched to execute simultaneous service, with the objective of minimizing the overall makespan. Given the combinatorial complexity of RPP-mTD, we propose a Hybrid Genetic Algorithm (HGA) that combines population-based exploration with targeted neighborhood searches. Solutions are encoded using a two-layer chromosome that represents: (i) an ordered, directed sequence of required edges, and (ii) their assignment to vehicles. A tailored segment-preserving crossover operator is introduced, along with multiple local search techniques to intensify the optimization. We benchmark the proposed HGA against established single truck-and-drone instances, demonstrating competitive performance. Additionally, we conduct extensive evaluations on new, larger-scale instances to demonstrate scalability. Our findings highlight the operational benefits of closely integrated truck-drone fleets, affirming the HGA's practical effectiveness as a decision-support tool in advanced mixed-fleet logistics.