Slotting optimization of warehouse based on hybrid genetic algorithm

Abstract

Traditional warehouse operation management always relies on experience to arrange inventory goods to available space once they arrived, resulting in the inefficient warehouse work. This paper considers goods' turnover rate and shelves' stability as principles to construct a multiobjective optimization mathematical model. By setting up random goal weight to improve traditional genetic algorithm, and based on MATLAB software platform to optimize the solution with mixed multitargets genetic algorithm. Taking the background of a specific warehouse position distribution to simulate and analysis. The result shows that this model is practical and effective. It can realize the reasonable distribution of the layout problem and reduce handling loss, as well as improve warehouse space utilization.