An Analysis of Optimization for Car PBS Scheduling Based on Greedy Strategy State Transition Algorithm

The differences in constraints between an automotive painting workshop and a final assembly can lead to production scheduling disruptions, using the Painted Body Store (PBS) manufacturing optimize meet requirements of workshop. This is achieved by establishing multi-objective mixed-integer optimization model for PBS solving state transition algorithm based on greedy strategy; finally, comparison was made with classical genetic algorithm. results show that optimal objective function when body sequence movement iterations data sets N R are 34 54, respectively. At this point, highest scores 23.46 49.79, vehicles entering system from painting-to-assembly line require 31 38 adjustments, Compared algorithm, simulation strategy significantly better; it also perform well discrete operations, demonstrating strong global search capabilities fast convergence. It provides new approach optimizing vehicle line.