Exploring Maritime Search and Rescue Resource Allocation via an Enhanced Particle Swarm Optimization Method

Author:

Sun Yang,Ling Jun,Chen XinqiangORCID,Kong Fancun,Hu QinyouORCID,Biancardo Salvatore AntonioORCID

Abstract

Maritime search and rescue (SAR) plays a very important role in emergency waterway traffic situations, which is supposed to trigger severe personal casualties and property loss in maritime traffic accidents. The study aims to exploit an optimal allocation strategy with limited SAR resources deployed at navigation-constrained coastal islands. The study formulates the problem of SAR resource allocation in coastal areas into a non-linear optimization model. We explore the optimal solution for the SAR resource allocation problem under constraints of different ship and aircraft base station settings with the help of an enhanced particle swarm optimization (EPSO) model. Experimental results suggest that the proposed EPSO model can reasonably allocate the maritime rescue resources with a large coverage area and low time cost. The particle swarm optimization and genetic algorithm are further implemented for the purpose of model performance comparison. The research findings can help maritime traffic regulation departments to make more reasonable decisions for establishing SAR base stations.

Funder

National Key R&D Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Foundation for Jiangsu key Laboratory of Traffic and Transportation Security

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

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