To improve the efficiency of the ballast water allocation of crane vessels and reduce energy consumption in this process, an optimization method following a multiobjective evolutionary algorithm based on decomposition (MOEA/D) is proposed.

Taking the water volume of each ballast tank after allocation as the decision variable, and the minimum total volume of allocated ballast water as the optimization objective, and introducing the constraint of floating state, a mathematical model for the ballast water allocation optimization of crane vessels is built. Aiming at the problems of slow solution speed and poor solution quality caused by the high dimensions of decision variables, an adaptive selection method for ballast tanks is proposed which greatly reduces the number of tanks involved in the adjustment. In light of the complex handling of constraint conditions, the single objective optimization is transformed into a multiobjective optimization problem, and the MOEA/D algorithm is then applied. The final results are selected from the Pareto solution set.

An example of ballast water allocation in the process of the crane slewing of a crane vessel is put forward. The calculation results show that the number of cabins involved in ballast adjustment is reduced by 27%, and compared with the NSGA-II algorithm and genetic algorithm (GA) algorithm, the total volume of allocated ballast water is reduced by 24% and 38% respectively, which verifies the feasibility and effectiveness of the MOEA/D algorithm.

The proposed method based on MOEA/D provides a new solution for the optimization of the ballast water allocation of crane vessels. It has certain engineering application value by offering a better ballast water allocation scheme.