Scheduling Problem of Empty Container Trucks Considering the Uncertainty of Bulk Cargo Weight at the Terminal

The scheduling problem of container trucks considering the uncertainty of bulk cargo weight has become an important factor hindering the efficiency of automated container terminals. To address it, a low-complexity and accurate control algorithm for truck routing problem under uncertain demands is proposed. Firstly, a tunable parameter called risk preference level was designed to precisely quantify the uncertainty of the planned routes in meeting clients’ demands. Secondly, a multi-stage heuristic algorithm, GA-SAA is designed, in which a low-complexity individual encoding and decoding method for uncertain demand is developed based on the risk preference level. Lastly, the costs of truck scheduling results were compared among GA-SAA, GA, SAA, and ACO at different risk preference levels, and GA-SAA shows its advantages over other algorithms.