Research on Scheduling Optimization Algorithm of Picking Job in Logistics Automated Warehouse Based on Chaotic Genetic Algorithm

Traditional warehouse operation management has followed the habit of many years, relying on experience to place goods, usually placing the goods in the nearest possible location, usually without taking into account the dynamic changes of goods and customers’ needs, resulting in problems such as slow process speed, low warehouse utilization rate and insufficient space utilization. As the core of warehousing system, automated warehouse has the characteristics of mechanization of access, informatization of process and rationalization of storage space, which has attracted more and more attention of modern enterprises. Aiming at the problems existing in the location allocation of enterprises, this paper puts forward a multi-objective storage location allocation model based on the principles of warehousing efficiency, roadway operation balance and adjacent similar products. The weight coefficient change method based on adaptive genetic algorith m is used to solve the model, and the algorithm is compared to verify the effectiveness. According to the solution method of multi-objective problem, the multi-objective optimization problem is transformed into a single objective optimization problem, which is solved by chaotic genetic algorithm, and a set of convergent feasible solutions are obtained.