Multimodal container slot allocation and pricing optimization with overbooking strategies

In the face of uncertain and diverse market demands, maximizing revenue for multimodal transport operators in limited circumstances is a critical challenge. This paper addresses the joint decision-making process of container slot allocation and dynamic pricing, incorporating an overbooking strategy based on revenue management theory from the perspective of multimodal transport operators. We formulate a two-stage stochastic programming model for this problem. Numerical experiments validate the model’s effectiveness, showing that overbooking resolves the conflict between limited capacity and revenue goals, significantly increasing operator revenue. Unlike previous studies, this work introduces a novel modeling framework that integrates overbooking into joint decision-making, offering a more realistic and comprehensive approach. These findings provide a viable solution for multimodal transport operators to increase their revenue and offer theoretical and practical insights for effective resource allocation in the market.