Optimization for a Multi-Constraint Truck Appointment System Considering Morning and Evening Peak Congestion

Gate and yard congestion is a typical type of container port congestion, which prevents trucks from traveling freely has become the bottleneck that constrains productivity. In addition, urban traffic increases uncertainty truck arrival time additional costs. More more terminals are adopting appointment system (TAS), tries to manage arrivals evenly all day long. Extending existing research, this work considers morning evening peak proposes novel approach for multi-constraint TAS intended serve both companies terminals. A Mixed Integer Nonlinear Programming (MINLP) based model formulated, explicitly change cost, queuing cost. The aim proposed minimize overall operation Lingo commercial software used solve exact solutions small medium scale problems, hybrid genetic algorithm simulated annealing (HGA-SA) obtain large-scale problems. Experimental results indicate can not only better but also effectively reduce their cost compared with traditional TASs.