Optimization of Multi-Port Empty Container Repositioning under Uncertain Environments

Empty container repositioning has always been an important problem faced by ports. In this paper, we study the multi-port empty container repositioning problem with the uncertainty of the demand and supply of empty containers in ports. First, we established an optimization model for empty container reposition strategies and calculated every port’s proportion, depending on its own empty container storage, on the operation of other ports and on the leasing company, in meeting the demand. Next, we established an optimization model for the empty container non-repositioning strategy, calculated the same proportions and compared their performance under two strategies. A two-stage particle swarm optimization (TS-PSO) algorithm was designed to solve the two models, and an example was used to verify the effectiveness of the algorithm and the rationality of the two models. Our research showed that the total cost of empty containers, storage costs, lease costs and the optimal storage of empty containers in ports under the repositioning strategy are all lower than those of the non-repositioning strategy. The proportion of the empty container demand met by inventory under the repositioning strategy is higher than that under the non-repositioning strategy, while the proportion of the empty container demand met by leasing is lower. The costs of leasing cost and repositioning empty containers are higher than those under the non-repositioning strategy. The increase in transportation time between ports per empty container mainly leads to the increase in the reposition costs of all ports. The increase in storage fees chiefly leads to the rising storage costs of all ports. The increase in leasing fees leads to the rising leasing costs of all ports. The paper provides a method for ports to decide the upper limit of empty container storage and to optimize their repositioning strategy.