Maritime patrol tasks assignment optimization of multiple USVs under endurance constraint

Abstract

Unmanned surface vehicles (USVs) are economic, have good maneuverability, and can perform some complex and high-risk tasks such as maritime supervision, leading to reduced costs and casualties. In this study, we investigate the application of USVs in maritime patrols, considering the endurance constraints of the USVs and the time constraints. Additionally, we establishes a mathematical model for optimizing the patrol path of multiple USVs under the endurance and time constraints. Considering the complexity of the model, the logistic map is introduced into the immune algorithm (IA) to improve the optimization. Then according to the relevant constraints, the corresponding coding and decoding methods are designed. Finally, the mutation and crossover operators of the genetic algorithm (GA) are combined with the designed IA to improve the diversity of antibodies in the iterative process, thereby improving the optimization ability of the algorithm. In the final numerical simulation experiment verification, the improved IA with GA (IA–GA) is compared with the traditional IA, GA, PSO-GA (Particle Swarm and Genetic hybrid algorithm) and IA–GA-greedy (IA–GA with greedy attribute) through simulations and case analysis. The results show that the improved IA can find a better solution than other algorithms in a reasonable time, which proves the superiority of the proposed algorithm.