The existing research of sequential zoning system and simultaneous zoning system mainly focuses on some optimization problems such as workload balance,product assignment and simulation for each system separately.But there is little research on comparative study between sequential zoning and simultaneous zoning.In order to help the designers to choose the suitable zoning policy for picker-to-parts system reasonably and quickly,a systemic selection method is presented.Essentially,both zoning and batching are order clustering,so the customer order sheet can be divided into many unit grids.After the time formulation in one-dimensional unit was defined,the time models for each zoning policy in two-dimensional space were established using filling curves and sequence models to link the one-dimensional unit grids.In consideration of “U” shaped dual tour into consideration,the subtraction value of order picking time between sequential zoning and simultaneous zoning was defined as the objective function to select the suitable zoning policy based on time models.As it is convergent enough,genetic algorithm is adopted to find the optimal value of order picking time.In the experimental study,5 different kinds of order/stock keeping unit(SKU) matrices with different densities d and quantities q following uniform distribution were created in order to test the suitability of sequential zoning and simultaneous zoning to different kinds of orders.After parameters setting,experimental orders inputting and iterative computations,the optimal order picking time for each zoning policy was gotten.By observing whether the delta time between them is greater than 0 or not,the suitability of zoning policies for picker-to-parts system were obtained.The significant effect of batch size b,zone number z and density d on suitability was also found by experimental study.The proposed research provides a new method for selection between sequential zoning and simultaneous zoning for picker-to-parts system,and improves the rationality and efficiency of selection process in practical design. The existing research of sequential zoning system and simultaneous zoning system primarily focuses on some optimization problems such as workload balance, product assignment and simulation for each system separately. There is little research on comparative study between sequential zoning and simultaneous zoning.In order to help the designers to choose the suitable zoning policy for picker-to-parts system reasonably and quickly, a systemic selection method is presented. Essentially, both zoning and batching are order clustering, so the customer order sheet can be divided into many unit grids.After the time formulation in one-dimensional unit was defined, the time models for each zoning policy in two-dimensional space were established using filling curves and sequence models to link the one-dimensional unit grids.In consideration of “U” shaped dual tour into consideration, the subtraction value of order picking time between sequential zoning and simultaneous zoning was defined as the objectiv e function to select the appropriate zoning policy based on time models. As it is convergent enough, genetic algorithm is adopted to find the optimal value of order picking time. In the experimental study, 5 different kinds of order / stock keeping unit (SKU) matrices with different densities d and quantities q following uniform distribution were created in order to test the suitability of sequential zoning and simultaneous zoning to different kinds of orders.After parameters setting, experimental orders inputting and iterative computations, the optimal order picking time for each zoning policy was gotten.By observing whether the delta time between them is greater than 0 or not, the suitability of zoning policies for picker-to-parts system were.The significant effect of batch size b, zone number z and density d on suitability was also found by experimental study. proposed proposed research provides a new method for selection between sequential zoning and simultaneous zoning for picker-to-parts system, and improves the rationality and efficiency of selection process in practical design.