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.