Inland Ports Location Problem With Uncertainty Demand And Supply

In recent years,the speed of globalization of economic development and territorialization in the world has been developing at a high state.As a hub connecting inland trade and a supporting platform for economic and trade exchanges,inland ports play an increasingly important role in coordinating the integrated distribution of inland and port logistics,participating in the allocation and transportation of inland hinterland economic resources.Inland port location problem is the most important in its scientific layout,planning and construction.It is the key to determine whether inland ports can play a role in reducing transport costs and alleviating traffic congestion in ports.However,the uncertainty of many factors in the planning period for inland ports makes the decision-making of location more complicated and difficult To solve this issue,this paper studied inland ports location under uncertain demand and supply,which can provide a basis for rational planning of inland ports,building a robust network of inland ports and realizing efficient ultilization of resources.After summarizing the related research of inland ports and analyzing the deficiencies,this paper studied inland port location with highway,railway and inland river multimodal transport network.Firstly,this paper studied inland ports location with demand determination,and a model of inland port location with minimum composite cost including construction cost,transport costs and path failure penatly cost as the objective function is constructed.According to the characteristics of the model and the merits and faults of various algorithms,a Simulated Annealing-Particle Swarm Optimization(SA-PSO)algorithm is designed to determine the location scheme in a specific demand situation,and at the same time,the optimal function value of the scheme is obtained.Secondly,the problem is extended,studied the problem of inland port location problem under double uncertain of demand and supply.The stochastic and robust inland ports location models are constructed respectively under double uncertainties-supply and demand.And the robust location model is based on the optimal value of the location model with determined-demand,minimizing the total cost and its deviation from the optimal value.Finally,the validity of the model and the algorithm is verified by an example.The result show that:(1)Compared with the deterministic location model,the stochastic location model and robust location model can cope with the impact of demand fluctuation on the location results;Compared with the stochastic location model,the robust location model can more effectively solve the impact of uncertainty on inland port location,reduce the maximum regret value in the worst case,and reduce investment risk.(2)Considering waterway transport in inland port collection and distribution network can not only reduce land traffic pressure,but also reduce transport costs effectively,provide more choices for cargo owners and reduce the loss caused by path failure.(3)The reliability of inland port system is inversely proportional to the penalty cost.The higher the reliability requirement,the smaller the penalty cost,which reduce unnecessary losses,but loses part of the transportation cost.Considering the uncertainty of supply,the system can respond immediately when the supply is interrupted and return to normal operation quickly,which has a significant effect on reducing the loss of risk to all participants in inland port system.(4)The fluctuation of transport cost discount coefficient in inland ports system has a great influence on the change of total cost,and it also has some influence on the result of inland port location.Accurate grasp of transportation cost and discount principle in the stage of location planning is the key to reduce the logistics cost of inland port system.