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Abstract
This paper focuses on the optimization of container shipping network and its operations under changing cargo demand and freight rates. The problem is formulated as a mixed integer non‐linear programming problem (MINP) with an objective of maximizing the average unit ship‐slot profit at three stages using analytical methodology. The issues such as empty container repositioning, ship‐slot allocating, ship sizing, and container configuration are simultaneously considered based on a series of the matrices of demand for a year. To solve the model, a bi‐level genetic algorithm based method is proposed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms. The obtained results show that the suggested model can provide a more realistic solution to the issues on the basis of changing demand and freight rates and arrange a more effective approach to the optimization of container shipping network structures and operations than does the model based on the average demand.