Optimization study of stacker cranes path in logistics distribution center

In order to improve the efficiency of stacker cranes in automated three-dimensional warehouses, an improved simulated annealing algorithm is investigated to optimize the path of stacker cranes. First, a mathematical model with the objective of the shortest access time is established, and the constraint of the maximum loading capacity of the stacker cranes is added. Then, on the basis of simulated annealing algorithm (SA), a genetic algorithm (GA) with strong global search ability is introduced into the simulated annealing algorithm to expand the search range of the solution, and a hybrid simulated annealing genetic algorithm (SAGA) is obtained. Finally, the simulated annealing genetic algorithm is simulated using Matlab in combination with practical application case studies. Through experimental calculations, when using the hybrid genetic algorithm to control the stacker cranes to access the goods, the travel distance of the stacker cranes is better than when using the simulated annealing algorithm, which reduces the time by 13.06% compared with the simulated annealing algorithm, and effectively improves the efficiency of the goods out of the warehouse.