Solving integrated problem of stowage planning with crane split by an improved genetic algorithm based on novel encoding mode

Abstract

Stowage plan, which is planning for a reasonable movement of containers, plays an important role in enhancing the efficiency and competitiveness of container terminals. The time required for handling containerships also depends on the operations of quay cranes, which is one of the most expensive equipment in container terminals. Hence, this paper integrates stowage planning and crane split problem to minimize the total berthing time at each visiting port over the voyage. A new mathematical model is developed, which covers a wide range of operational and structural constraints for both stowage plan and crane operation. An improved genetic algorithm based on a novel encoding mode of assignment strategies, including container grouping and operation strategies, is designed to solve the problem, which also introduces penalty operations to solve the infeasible solutions. Finally, some computational experiments are carried out. Firstly, three small-sized experiments are implemented to verify the feasibility of the proposed model and algorithm. Secondly, large-sized experiments with 5 ports, 3385 containers, and 2 quay cranes show that the proposed approach can solve the integration problem with different productivity of quay cranes effectively and decrease the berthing time by 6.0%. Eventually, a comparison experiment with 5 ports, 5752 containers, and 2 quay cranes is conducted, and the results indicate that the proposed algorithm results in 62.3% and 87.7% decrease in the total number of rehandling times and computational time. Meanwhile, the results also show that the proposed algorithm can be convergent. So the proposed algorithm is effective and efficient in solving the integration problem and enhancing the efficiency of container terminals.