Research on berth allocation and scheduling optimization of container terminal based on intelligent algorithm

In this paper, an optimization method based on intelligent algorithm is proposed to solve the problem of berth allocation and scheduling in container terminals. Berth allocation and scheduling, as the core link of terminal operation management, has a direct impact on the throughput, ship waiting time and operating cost of the terminal. Traditional methods rely on empirical judgment and simple rules, and it is difficult to adapt to the complex and changeable operating environment of modern terminals. Therefore, this study developed an optimization model based on the Genetic Algorithm (GA), achieving efficient optimization of berth allocation and scheduling through encoding design, fitness function evaluation, and genetic operations such as selection, crossover, and mutation, combined with a local search optimization strategy. Experimental results show that GA significantly outperforms First-Come-First-Served (FCFS) and Simulated Annealing (SA) algorithms in terms of average vessel waiting time, berth utilization rate, and priority satisfaction rate. Parameter sensitivity analysis further confirmed the impact of population size and mutation probability on algorithm performance, identifying the optimal parameter configuration.