Research On The Ships' Scheduling Of Z Shipping Company

Nowdays, saving logistics cost is becoming the third profit source besides labors and natural resources as the development of economic increasing globlization, which is the precondition and guarantee of a enterprize production. Ships' scheduling is an important factor that relates with transportaiton profit and integrated optimization of the fleet, which further affects an enterprize's ability of challenge, survival and development. Based on the provided research, this paper has done some extended and systematic research on the scheduling problem of Z company.Scheduling is one of the main bottlenecks which restrict the quarlity & efficiency of feederline container ships transportation. This paper extended overland vehicle routing problem (VRP) model, to take the smallest total navigation cost of all the scheduled ships as the objective function, and to consider some practical facters such as time restriction, and proposed the feederline container ships scheduling model for the hub_spoke maritime transportation system, which contains a hub port and many feeder ports and is charactered by multi-navigation lines and multi-ship types. According to the character of this problem's solution, a particle swarm optimization(PSO) algorithm was designed to find the near-optimal solution of the model.As the kernel of transfer logistics platform operations, the scheduling problem of a bulk barge is one of the bottlenecks which restrict the operation's efficiency and cost per TEU. Based upon the working flow of the transfer logistics platform, three main practical constraints, inventory capacity, sailing schedules and service priority, are considered to aim at the smallest total weighted time and lowest operation cost per TEU in this paper. A bi-objective programming scheduling model is proposed. According to the character of the solution, a genetic algorithm is designed to find the near-optimal solution of the model.Case studys and experimental analyses were conducted to show their rationality and efficiency of the models and algorithms proposed. So a conclusion can be drawn that the research of this paper can offer decision support for the ships' scheduling of Z company.