Application of Hybrid Optimization Algorithm Considering Yard Priority to Port Vehicle Scheduling

With the increasing scale and complexity of port logistics, the Vehicle Routing Problem (VRP) has become a key challenge to improve the efficiency of port logistics with multiple ships and multiple yards. In this paper, a hybrid method based on ant colony optimization algorithm and genetic algorithm is proposed for optimizing the vehicle scheduling problem in port cargo transportation. The study is designed to construct the fitness function by considering the transportation time, fuel consumption, yard priority and the number of vehicle turns, aiming to minimize the transportation time and fuel consumption, while giving priority to meet the cargo demand of yards with higher inventory. The algorithm improves the global optimization capability of path search by introducing the pheromone matrix updating mechanism combined with the crossover and mutation operations of the genetic algorithm.