Research On Route Optimization Of Very Large Crude Carrier Route Based On Particle Swarm Optimization

The globalization of the world economy has led to the rapid growth of international cargo transportation,and maritime transportation accounts for more than 80% of the trade transportation.However,with the increase of fuel price and the improvement of IMO carbon emissions,which route optimization is an effective means to improve the energy utilization and economic efficiency of vessel operation.Therefore,on the premise of navigation safety,it is of great significance to optimize the ship route with comprehensive consideration of voyage time and fuel consumption.Comprehensive consideration of weather and constraints to a ship of very large crude carrier as the research object,and the mathematical model of ship route intelligent optimization was established.Using Python language,a multi-objective ship route optimization program based on particle swarm algorithm and Pareto optimal solution was developed.Based on the authentication model,taking the great circle route and the historical route of a ship of very large crude carrier as a reference,and comparison analysis under different single objective and multi-objective method proposed in this paper on energy conservation and emissions reduction and improve the economic benefit of the ship in terms of potential.According to the different planning the most economical shipping routes for shipping market,to provide technical support for the ship operating companies.Research shows that the error of static water resistance model under full load condition is less than 3%,and the trend of wind wave additional resistance model is correct.Under the target of minimum fuel consumption,the total fuel consumption of the optimized route is 15.2t lower than the historical track,and the fuel saving rate of single voyage is 1.51 %,which can save 425.6 t fuel throughout the year and significantly reduce fuel consumption.Under the objective of the shortest sailing time,the optimized route shorted the actual sailing time of the historical track by 11.3 h.The cargo arrival time is earlier and the annual sailing time reduces the sailing time by 327.7 h,providing an optimized solution for the selection of routes when the capacity is tight.When considering both the lowest fuel consumption and the shortest flight time objectives,the optimization of Pareto optimal solution set of optimal compromise routes voyage ETA300.3 h,the total fuel consumption of the voyage is 995.3 t.Which is compared with the minimum fuel consumption route the sailing time is shortened by 1.9 h,and compared with the shortest sailing time route,it saves 9.1 t of fuel,achieving a balance between fuel consumption and voyage time.Under the recent shipping market,the total cost of a single voyage in the most economical route in the Pareto optimal solution set is US$ 649,111.2,which is a savings of US$ 10131.7 compared to the total cost of historical routes.In addition,under any extreme market conditions,Pareto optimizes the total cost of single voyage,which is lower than the total cost of historical route.The realization of ship route optimization based on particle swarm algorithm provides technical support for decision makers to choose the best route according to sea conditions and market conditions.