Deng Qingwen
ABSTRACT
Entering the high-speed development of the world economy since the 21st century and the large circulation of commodities and goods, the logistics industry has become one of the most important sectors in economic construction. As a result, the prosperity of the logistics industry has led to improved labor costs. However, it has gradually been unable to meet market demand. At the same time, the rapid advancement of industrial automation has made industrial robots gradually replace the roles of traditional labor in packaging, welding, logistics, and other sectors. In response to this situation, the researcher decided to combine the directions of C++ programming language, optimization algorithms, predictive analytics technology, and their robotic applications. The researcher developed a box-type cargo automated car loading robot with external enterprises and created a decision-supported logistics and transportation loading system tailored to the robot’s characteristics. By integrating logistics transportation loading systems with decision-making support, which aimed to address issues such as boxing tasks, low efficiency, and high labor costs in the current box-type cargo loading processes within the logistics industry.
Keywords: Decision support systems, logistics and transportation loading, optimization algorithms, predictive analysis robotics