Vessel Routing Chance-constrained Multi-objective Optimization by LNG and Diesel Hybrid Energy Vessels for Marine Debris Collection

Abstract Marine debris causes great harm to the ecosystem and human health, and it is urgent to clean up marine debris. In this paper, the method of logistics network is adopted to optimize the vessel route for debris collection. In order to reduce carbon emissions, we use LNG hybrid energy vessels. Since debris weight is difficult to predict, we treat it as a random variable. Considering the relationship among the three factors: speed, travel time, and carbon emissions, a multi-objective chance constraint model is established, and then transformed into a deterministic model by distribution function. We also design an AM-PHALNS algorithm using the AMOSA algorithm as a framework. Finally, through the case analysis of waste collection in the East China Sea, it is verified that the AM-PHALNS algorithm is superior to the NSGAII algorithm, saving 13.55% of travel time, 18.52% of total carbon emissions, and 20.25% of running time on average.