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Bi-level programming enabled design of an intelligent maritime search and rescue system
Affiliation:1. Sanjiang Research Institute of Artificial Intelligence and Robotics, Yibin University, Sichuan, China;2. Department of Logistics & Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hong Kong;3. School of Management, Shanghai University, Shanghai, China;4. School of Built Environment, College of Sciences, Massey University, Auckland, New Zealand
Abstract:This paper studies an intelligent maritime search and rescue (SAR) system problem. According to historical accidents and available SAR equipment information, a bi-level mixed-integer programming (MIP) model is proposed to determine the type and number of SAR equipment allocated to activated stations. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) algorithm are applied to solve the proposed mathematical model. Computational experiments based on real instances in the East Sea China not only validate the effectiveness of the bi-level MIP model in balancing two objectives during decision process, but also indicate that PSO algorithm is better than GA algorithm to solve the proposed model and generate reasonable equipment allocation plans. Some managerial implications are also outlined on the basis of the numerical experiments.
Keywords:Maritime search and rescue  Equipment allocation  Bi-level  Particle swarm optimization  Genetic algorithm
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