Application of weight coefficient searching genetic algorithm in the plan generation of cargo loading and unloading for liquid cargo carrier - Ming QI; Jiahao LIN; Miao SUN; Yong ZHANG (Zhongguo Jianchuan Yanjiu, 2022)
ObjectiveCargo loading and unloading plan generation time and safety evaluation have a great influence on the handling efficiency. To this end, this paper introduce weight coefficient searching genetic algorithm into the plan generation. MethodsLoading safety status mainly involves draft limitation, intact stability checking, hyrostatic strength checking and compatibility between the generated loading and unloading plan and preset process. In this study, a non-deterministic polynomial and corresponding optimization objective functions are established to solve the loading and unloading scheme generation problem of liquid cargo carriers. The weight of each influence factor in the objective function is changed and recorded in sequence to form an optimal objective function cluster. The optimal solution of each member in the cluster is then carried out through an elitist preservation genetic algorithm in order to provide an optimal solution set. On this basis, a comparison is made with the loading and unloading plan of a very large crude oil carrier (VLCC) generated by the linear fitting methodResultsThe ship draft status is more consistent with the target, and the stability state is obviously better than that of the user preset plan in each loading/unloading step generated by this algorithm. ConclusionThe weight coefficient searching genetic algorithm based on elitist preservation proposed in this paper can improve the accuracy and reliability of the liquid cargo carrier loading sequence.