Simulation Optimization of Tobacco Sorting System Based on Genetic Simulated Annealing Algorithm

The sorting system is the core of the tobacco logistics distribution center, the current distribution center cigarette sorting volume is large, and different order sorting orders have a greater impact on the total processing time of the order, to improve the sorting efficiency of the tobacco logistics distribution center, the establishment of a mathematical model to minimize the total time of the delay of the order as the objective function, the use of improved adaptive genetic annealing algorithm for the solution, and the use of Plant Simulation software to establish a simulation model of the sorting system, the results of the solution in Plant Simulation software simulation verification, it is verified that the use of the algorithm for order sorting, compared with the traditional sequential sorting, effectively reduces the total processing time of the order sorting, and improves the sorting efficiency of the tobacco logistics and distribution center.