Abstract: At present,in order to further improve the customer satisfaction of inland waterway terminals,operational decisions such as berth plans need to fully consider the ship’s costs,revenues and other indicators,so this paper,in order to solve the problem of the joint allocation of berths and shore bridges,establishes a mixed-integer planning model with the minimization of the sum of the carbon emission cost of the port and the cost of the ship’s presence in the port as the objective function;and at the same time,considering the effect of the tide factor on the allocation of berths of the inland waterway terminals,in the model tidal constraints are added into the model.In order to improve the applicability of the algorithm to solve the model,this paper improves the particle swarm algorithm and designs PSO-GA mixed row optimization algorithm,which adopts the crossover and mutation operators of the genetic algorithm to realize the intelligent regulation of the population evolution during the optimization process,so as to improve the accuracy and superiority of the optimization.Finally,this paper validates the algorithm with examples based on the actual data of a container terminal,and then the optimized validation results of the algorithm are compared with the traditional genetic algorithm and particle swarm algorithm to reduce the total cost by about 12.5% and 11.3%,respectively,which proves the superiority of the algorithm and the feasibility of the model.