Study On Optimization Of Tug Dispatching In Port

Harbor tug is an important tool for ships to enter and leave the harbor and assist large ships to complete berthing,leaving and shifting.It can be seen that the improvement of the efficiency of tugboat operation in the port can reduce the waiting time of ships arriving at the port in the anchorage or berth,so as to improve the rate of ships' arrival and departure from the port,which not only improves the economic benefits for the port and the ship company,but also greatly improves the ship company's satisfaction with the port.With the development of the port,the ship an increase in the number of roads,the use of port tug is also increasing,at present,most of the ports used by port tug scheduling scheme is only rely on the historical experience,established by the scheduling scheme,it is difficult to ensure the vessels' quick smoothly in and out of port,so how to according to the complicated and changeable situation roads to specify the tug of reasonable scheduling scheme,many ports have become the current urgent needs to solve one problem.In fact,the scheduling problem of harbor tug is a combinatorial optimization problem between harbor tug and arrival ship,which is not a traditional scheduling problem but anp-hard problem.Therefore,it is difficult to solve it by using conventional mathematical programming method.At present,the commonly used intelligent optimization algorithm has been widely used in the field of scheduling problem because of its excellent searching ability.However,the advantages and disadvantages of each algorithm are different,so the scheduling problem suitable for solving is different.In this paper,the scheduling problem of harbor tug is a nonlinear,discrete and the gradient information of the objective function is not clear enough.The particle swarm optimization algorithm selected in this paper has the advantages of fast search for the optimal solution,storage and sharing of the historical experience of individuals and groups and simple parameter setting,which makes the particle swarm optimization algorithm have better optimization effect in solving the tugboat scheduling problem.In this paper,the specific characteristics of harbor tugboat work as a reference basis,the establishment of harbor tugboat scheduling model,the traditional standard particle swarm optimization algorithm to improve,and combined with Dalian harbor tugboat daily work examples,then the algorithm and model were verified,and the establishment of a tugboat scheduling platform.The work mainly includes the following aspects:(1)The tugboat scheduling problem is analyzed and the mathematical model of the tugboat scheduling problem conforming to the situation of Dalian port is established.(2)The commonly used intelligent optimization algorithm is analyzed,and the relevant knowledge of particle swarm optimization is mainly introduced.The real number coding strategy,elite set and crossover mutation method are used to optimize the particle swarm optimization algorithm.(3)Carry out simulation with MATLAB software,verify the designed algorithm and model with examples,and compare and analyze the resultsExperiments show that the algorithm designed in this paper not only has a significantly higher convergence rate than other algorithms,but also has a better optimal solution,which provides a scientific decision-making basis for the scheduling of tugboats in ports.