Improved NSGA-Ⅲ in multi-objective optimization of stowage planning for inland container ship

The diversity of inland container transportation requires multi-objective optimization in ship stowage planning. Aiming to satisfy the requirements of ship transportation economy and seaworthiness, a multi-objective optimization model for stowage of inland container ships is built. The model, based on NSGA-Ⅲ（Non-dominated Sorting Genetic Algorithm-Ⅲ）, is developed to comprehensively optimize the number of ship stacks, number of blocking boxes, stability height, roll angle and pitch value. For effectively solving the problem, the grey-entropy parallel analysis method is used to improve the NSGA-Ⅲ algorithm, and the grey entropy parallel correlation degree is used as the guidance algorithm of fitness value for elite selection. The advantage of the algorithm and its robustness are demonstrated.