Research on genetic algorithm-based simulation of dynamic container truck scheduling

Targeting at the truck scheduling in the process of container terminal operations, a dynamic truck scheduling model with strong applicability is designed to reduce truck-load rate, and shorten the time of handling task. According to the model characteristics, improved genetic algorithm is used to solve it, and determine the parameters suitable for this model including population size, fitness function, selection criteria, crossover probability and mutation probability, etc. Combined with specific cases, MATLAB is applied for simulation to verify the feasibility and effectiveness of the model and algorithm proposed by this paper.