Abstract: Changes of internal and external environment make slotting optimization to automated warehouse very necessary and important. Among slotting optimization study,there is not a valid distinction between the characteristics of automated warehouse cargo space and storage spaces,and there is a lack of the establishment of dynamic optimization model analysis before and after cargo space moving.Using the data before and after the movement that can record, considering three elements:improring the efficiency of the goods moving into and out of the warehouse, storing related products together, decreasing transportation time of moving products in the process of slotting optimization, a multi-objective model is put forth in this paper based on time. The simulation results of example solved by genetic algorithm using matlab show that this method can effectively achieve slotting optimization, recorded data before and after optimization can be effectively saved into the automated warehouse management system, and slotting optimization is an effective way to automated warehouse to reduce storage management costs, improve inventory management efficiency and effectiveness.

Key words: based on time automated warehouse, slotting optimization model, genetic algorithm