<p>The study analyzed the basic structure of supply chain logistics and explored key technologies and transportation cost estimation algorithms. By constructing a fitness function and evaluating the effectiveness of the algorithm, the overall framework of a hybrid manufacturing intelligent logistics optimization scheduling system was established, and the logistics optimization scheduling process and interference management scheduling model were elaborated in detail to cope with complex manufacturing environments. Strict performance testing was conducted on the constructed system, including evaluation of scheduling effectiveness and response time. The test results showed that the proposed scheduling algorithm has significant advantages in reducing costs and improving response speed. The effectiveness and feasibility of the algorithm were verified through simulation and data analysis. Finally, research has shown that the hybrid manufacturing logistics optimization scheduling algorithm based on artificial intelligence cannot only effectively improve the intelligence level of supply chain management, but also provide new ideas and methods for achieving efficient and flexible logistics scheduling.</p>