Research on intelligent vehicle shipyard scheduling based on improved sparrow algorithm

Ship block yard scheduling is of utmost importance in shipbuilding, as its efficiency directly impacts the construction cycle and logistics cost. Traditional scheduling, which hinges on manual experience, suffers from issues such as numerous blocking segments and high transportation costs. In this paper, a multi - constraint scheduling model aiming to minimize transportation cost is constructed. An improved sparrow algorithm (ISSA) is proposed, integrating chaos initialization, butterfly search, and triangle walk strategy. Moreover, intelligent vehicles are introduced into the scheduling process. Their application is expected to enhance the flexibility and intelligence of material transportation. The effectiveness of the algorithm is verified through simulation experiments, and the influence of yard layout on scheduling results is revealed. The overarching goal is to optimize the task execution sequence and storage allocation strategy, thereby reducing transportation cost and improving scheduling efficiency.