For the problems of encountering and overtaking in the process of in-and-out port of ships in the container terminals with two-way channel, a new ship dispatching optimization algorithm focusing on the service rules was proposed. Firstly, the realistic constraints of two-way channel and the safety regulations of port night sailing were considered at the same time. Then, a mixed integer programming model with the goal of minimizing the total waiting time of ships in the terminal was constructed to obtain the optimal in-and-out port sequence of ships. Finally, the branch-cut algorithm with embedded polymerization strategy was designed to solve the model. The numerical experimental results show that, the average relative deviation between the result of the branch-cut algorithm using embedded polymerization strategy and the lower bound is 2.59%. At the same time, compared with the objective function values obtained by the simulated annealing algorithm and quantum differential evolution algorithm, the objective function values obtained by the proposed branch-cut algorithm are reduced by 23.56% and 17.17% respectively, which verifies the effectiveness of the proposed algorithm. The influences of different safe time intervals of ship arriving the port and ship type proportions were compared in the sensitivity analysis of the scheme obtained by the proposed algorithm, providing the decision and support for ship dispatching optimization in container terminals with two-way channel.

The ship scheduling affected by severe weather is a very complex optimization problem, and is also one of the key issues needed to pay attention in liner companies. Therefore, based on the premise of obtaining the latest weather forecasting information in the designed multi-stage rescheduling mechanism period and the real-time positions of all the ships in service in one liner company on a shipping network, the restriction of liner shipping schedule was focused on, and the realistic constraints such as the change of ship's speed between different ports and the ship capacity, a nonlinear mathematical model was built to minimize the total shipping cost of all the ships during the fixed planning period. And an improved genetic algorithm embedded with gene repair operator was designed to solve the built model. Then the optimal multi-stage rescheduling scheme, which was integrated by the solution strategies of charting for direct-transport, dispatching ship across different routes, adjusting port reaching order and goods transfer, was given. Experimental results of examples with large, medium, and small scales show that, compared with the traditional waiting method, multi-stage rescheduling saves more than 15% of the total shipping cost, verifying the effectiveness of the proposed model and scheme; compared with Cplex, the improved genetic algorithm has the calculation efficiency greatly improved and all the deviation values within 5%; and compared with Ant Colony Optimization (ACO) algorithm, Tabu Search (TS) algorithm, Quantum Differential Evolution (QDE) algorithm, the improved genetic algorithm has the cost reduced by about 10% in the effective time, proving that the algorithm is scientific. It can be seen that the proposed method can provide the reference for actual ship scheduling of liner companies.

The multi-type liner scheduling problem in liner enterprises caused by the fluctuation of cargo demand and tide with line schedule announced in advance was studied. Firstly, the structure of near-sea transportation routes of a liner enterprise was systematically analyzed. Then, with the consideration of the real situations like large ships need to tide in and out of ports, ship renting is permitted under appropriate conditions, and the limits of a liner schedule, a nonlinear programming model of multi-type liner scheduling was built with the objective of minimizing the total transportation cost. Finally, in view of the characteristics of the model, an Improved Genetic Algorithm (IGA) embedded with gene repair was designed to solve the problem. Experimental results show that the proposed liner scheduling scheme can improve the ship utilization ratio by 25%-35% compared with the traditional experiential liner scheduling scheme, the CPU processing time of IGA is reduced by 32% on average compared with CPLEX in medium scale, and the transportation cost of IGA is reduced by 12% on average compared with ant colony algorithm in medium and large scales. All above demonstrates the validity of the proposed model and algorithm which can provide a reference for liner enterprises in liner scheduling.

This paper proposed a liner programming model to deal with the Quay Crane (QC) allocation and scheduling problem for single ship under the circumstance of fixed berth allocation. With the aim of minimizing the working time of the ship at berth, the model considered not only the disruptive waiting time when the quay cranes were working, but also the workload balance between the cranes. And an Improved Ant Colony Optimization (IACO) algorithm with the embedding of a solution space split strategy was presented to solve the model. The experimental results show that the proper allocation and scheduling of quay cranes from the model in this paper can averagely save 31.86% of the crane resource compared with full application of all available cranes. When comparing to the solution solved by Lingo, the results from IACO algorithm have an average deviation of 5.23%, while the average CPU (Central Processing Unit) computational time is reduced by 78.7%, which shows the feasibility and validity of the proposed model and the algorithm.