Synchromodal transport planning with flexible services: Mathematical model and heuristic algorithm

As a critical feature of synchromodal transport (ST), service flexibility plays an important role in improving the utilization resources to reduce costs, emissions, congestions, and delays. However, none existing studies considered flexible services under framework synchromodality. This paper develops Mixed Integer Linear Programming (MILP) model formulate ST planning. In MILP model, vehicles with as well fixed are both considered, vehicle routes request planned simultaneously. Due computational complexity, Adaptive Large Neighborhood Search heuristic is designed solve problem. Several customized operators based on characteristics studied The proposed compared models developed highly-cited newly published that do not consider flexibility. Case small instances verified performs better all scenarios, including scenarios different weights for individual objectives, congestion,and dynamic optimization scenarios. On large (up 1600 shipment requests), reduces cost by 14% average literature.