Abstract: Aiming at the problems of chaotic storage allocation and low storage efficiency in automated three-dimensional warehouse, we proposed a combinatorial optimization model solved by a multi population space mapping genetic algorithm. The method improved the basic genetic algorithm and optimized the objective function composed of goods demand, shelf center of gravity and goods correlation. The MATLAB simulation results show that the method obtains better results than the existing algorithms, the values of the three objective functions are improved, and the task capacity can affect the optimization ability of the improved method.

Key words: storage allocation, combinatorial optimization, multi objective function modeling, genetic algorithm