Modeling an On-Time and Reliable Intermodal Routing Problem for Time-Sensitive Cargoes Considering Cargo Damage and Uncertain Demand

This study investigates a novel on-time and reliable intermodal routing problem for time-sensitive cargoes. Three practical factors, hard time window, damage costs, and fuzzy demand, are fully integrated into the problem optimization to achieve comprehensively improved route planning for time-sensitive cargoes. Using triangular fuzzy numbers to model the cargo demand uncertainty and induced cost and time uncertainty, this study proposes a fuzzy linear routing model to address the proposed problem, in which minimizing the total costs, consisting of transportation costs and damage costs, is formulated as the optimization objective. Furthermore, chance-constrained programming with a credibility measure is adopted to reformulate the proposed model to obtain an equivalent crisp linear representation that can be easily solved by the Branch-and-Bound algorithm to obtain the global optimum solution. A numerical case study is designed to verify the feasibility of the modeling. It indicates a trade-off between lowering the total costs and improving the reliability of transportation by increasing the confidence degree, and also demonstrates the feasibility of embedding damage costs into the optimization. Finally, it presents systematic sensitivity experiments to reveal the influence of the key parameters on the routing optimization for time-sensitive cargoes, and provides managerial implications for both the cargo owner and intermodal operator to effectively organize an on-time and reliable intermodal transportation that can achieve economic benefits and preserve cargo integrity.