Research On Site Selection Of Maritime Rescue Base And Optimization Of Rescue Ship Configuration

In recent years,with the rapid development of China’s economy,maritime trade has become more and more frequent.Due to the complex maritime conditions and changeable weather,maritime accidents often occur.In order to effectively improve the efficiency of maritime rescue,this paper applies scenario planning to the location of maritime rescue base and the optimization of rescue ship configuration,considers a variety of rescue ship types and the navigation area of each ship type,selects several ports and island along the line to establish rescue bases,and provides a certain number of rescue ships for the rescue base,so as to rescue the victims in time.Firstly,a certain sea area is divided into several water area units to determine the coordinates of risk points.Aiming at several water area units,some key water area units are determined according to previous maritime accidents and TOPSIS method.Some rescue bases should be set up in ports along the line and some rescue vessels should be equipped to cover the whole water area comprehensively,including key water areas for multiple times.Secondly,in the aspect of model construction,this thesis established a two-stage stochastic programming model,and assumed four emergency scenarios,including fog weather,typhoon weather,lightning weather,hurricane weather,and the construction cost of the maritime rescue base,The objective is to minimize the operating cost and construction cost of the ship as well as the cost of the delay in rescuing the risk point and the penalty cost of the unmet demand point.The immune particle swarm optimization algorithm is designed to solve the problem.Then in terms of case analysis,in the south China sea,for example,will be divided into several waters of the south China sea waters unit,unit,and determine the key waters along the port and part of the island as the candidate points of rescue base,through two-stage stochastic programming model and immune particle swarm optimization(pso)algorithm to determine the rescue base location location and the amount and type of ship.Finally,the main conclusions of this thesis are as follows: considering a variety of rescue ship types,a two-stage stochastic programming model is established.In the first stage,the location of the rescue base is selected.In the second stage,after determining the location of the rescue base,each rescue base is equipped with rescue ships to deal with emergencies at sea.Then,an immune particle swarm optimization algorithm is designed,taking the South China Sea as an example,Collect the location data of ports and the data of accidents in the history of the South China Sea.After repeated calculation,finally establish rescue bases in Shantou port,Humen Port,Yangjiang port,Zhanjiang port,Haikou Port,Sanya port,Sansha port,Huangyan Island and other ports,which can basically meet the needs of disasters in the South China Sea and verify the feasibility of the model and algorithm.Compared with the ordinary particle swarm optimization algorithm,the immune particle swarm optimization algorithm applied in this thesis is more suitable for the two-stage stochastic programming model in this thesis.It has higher efficiency,smaller objectives and shorter calculation time to solve the approximate optimal solution of the problem.Finally,the sensitivity analysis of the results shows that when the marine risk in the South China Sea increases,the marine rescue ship should be the focus of future investment,followed by fast rescue ship and high-speed rescue boat,which is more in line with the actual situation of the South China Sea.At the same time,it also provides a new direction for China’s South China Sea Rescue Bureau.