Research On Order Batching Based On Genetic Algorithm

Order batch picking is one way of order picking. This method puts several orders together, and then picks them at the same time. Its aim is to reduce the sorting and the handling of the average walking distance and time. In all the operations of a distribution center the cost of picking operations accounts for 60%-80% of the total cost, and labor accounts for 60% of all. Meanwhile, any mistake from picking operations could lead to customer dissatisfaction and high cost. This shows that the optimization design of the picking operation plays a very important role in distribution center.This paper researches the order batch picking problem in a manual picking distribution centers, combined with domestic and foreign research results. Based on certain assumptions, this paper gives the mathematical model, whose objective function is to minimize the cost of the order picking.As the order batch picking problem is a NP hard problem, this paper solves it using genetic algorithms. Genetic algorithm has powerful global search capability, and can find the relatively optimal solution in a large-scale solution space. Also, the use of genetic algorithm is characterized as an implicit parallel processing and strong robustness, which can reduce the time of solving problem and improve the solving efficiency. This will not only meet the daily management of enterprises but also get accurate result.At last, this paper does experiment simulation using ten days real data from a medical distribution center. Through the preparation with the traditional FCFS way, this paper proves that order batch picking is better than the traditional way. It means the order batch picking has a good application prospects.