Maritime container shipping fleet deployment considering demand uncertainty

Abstract

This paper investigates the integrated planning problem of fleet deployment considering demand uncertainty for container shipping liners. In the daily operation of container shipping networks with multiple routes, the demand of container transportation may exceed the capacity on some routes due to demand uncertainty. Shipping liners can apply temporary chartering and transshipment strategies to get extra capacity so that the excessive demand can be met. To formulate the problem, this paper develops a mixed-integer linear programming model to determine the fleet deployment, service scheduling, container routing and temporary chartering considering demand uncertainty. An improved particle swarm optimization algorithm is designed for solving this problem in large-scale cases. Numerical experiments show that the algorithm can solve the problem with high efficiency. This paper provides shipping liners with an integrated decision support tool for fleet deployment.