Optimization of Order Picking Path in Warehouse-type Supermarket under B2C Mode
At present,warehouse-type supermarkets in China rely completely on the B2C business mode for online and offline sales.As one of the core activities of B2C e-commerce,sorting occupies a large part of time and fund of the supermarkets.Warehouse-type supermarkets have both the storage function of a ware-house and the shopping function of a supermarket.Compared with traditional warehouses,the supermarket venue is irregular in layout,mainly manifested in floor plan,shelf type and placement direction.Since letting the sorting operation take up the store aisle for too long will affect the offline shopping experience of the cus-tomers,the timely and efficient identification and picking of goods is of great significance for the warehouse-type supermarkets to optimize their B2C mode and resources,enhance corporate competitiveness and improve customer satisfaction.In this paper,in combination with a summary of existing research literature on ware-house-type supermarkets,we introduced the characteristics of the order picking operation in warehouse-type supermarkets under the B2C mode.More specifically,the order picking process in warehouse-type supermar-kets under the B2C model is similar to that of traditional warehouses,that is,the system receives purchase or-ders placed by online customers via self-brand mall app or third-party shopping platform,then transmits the order picking information in batch to picking operators through a mobile terminal or in paper copy,and the operators will pick the goods and send them to the packaging station,which ends the warehouse picking pro-cess.Taking into account the irregularity of the warehouse venue,in order to reduce the moving distance of the picking operators,we put forward two sorting path optimization schemes from the perspective of picking port quantity and starting/ending picking points,and through environment modeling,established a batched or-der sorting path model with load and capacity restrictions.According to the model,in the batching stage,fac-tors such as emergency orders,product types,and delivery distance were taken into consideration,and a seed al-gorithm was used to solve the model;in the sorting stage,the polynomial mutation and simplex method with random perturbation were introduced to improve the sparrow search algorithm(SSA)to solve the model.Then,through simulation and case comparison,it was verified that measures such as increasing the number of picking ports,batching before picking,and allowing operators to select different starting and ending points dur-ing operations could reduce the number of operators to complete the sorting operation,reduce the in-ware-house picking time and improve equipment utilization,and that the improved sparrow search algorithm(ISSA)was better than the original algorithm in solving the model.Finally,the following conclusions were drawn:(1)The batching results obtained could prove that the batching method formulated in the plan could allow emer-gency orders to be prioritized,which could improve the utilization rate of picking equipment while reducing the number of operators and equipment,which could help the warehouse-type supermarkets coordinate B2C mode resources and reduce operating costs.(2)The improved sparrow search algorithm was superior to the original algorithm in terms of traveling path,which could reduce the walking distance of the operators in the warehouse,shorten the occupation time of the store aisle,and improve the order picking efficiency in the store and the satisfaction of offline customers.
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