Order picking is the part with the highest proportion of operation cost and time in the warehouse. The characteristics of small-batch and multi-frequency current orders reduce the applicability of the traditional layout in the warehouse. Besides this, the improvement of the layout will also affect the picking path, such as the Chevron warehouse layout, and at present, there is a lack of research on order picking with multiple picking locations under non-traditional layouts. In order to minimize the order picking cost and time, and expand the research in this field, this paper selects the Chevron layout to design and describe the warehouse layout, constructs the picking walking distance model of Return-type, S-type and Mixed-type path strategies in the random storage Chevron layout warehouse, and uses the Cuckoo Search (CS) algorithm to solve the picking walking distance generated by the Mixed-type path. Compared with the existing single-command order picking research, the order picking problem of multi picking locations is more suitable for the reality of e-commerce warehouses. Moreover, numerical experiments are carried out on the above three path strategies to study the impact of different walking paths on the picking walking distance, and the performance of different path strategies is evaluated by comparing the order picking walking distance with the different number of locations to be picked. The results show that, among the three path strategies, the Mixed-type path strategy is better than the Return-type path strategy, and the average optimization proportion is higher than 20%. When the number of locations to be picked is less than 36, the Mixed-type path is better than the S-type path. With the increase of the number of locations to be picked, the Mixed-type path is gradually worse than the S-type path. When the number of locations to be picked is less than 5, the Return-type path is better than the S-type path. With the increase of the number of locations to be picked in the order, the S-type path is gradually better than the Return-type path.

In order to improve the picking efficiency of warehouses, shorten the time cost and promote the development of the logistics industry, this study analyzes the routing strategies in fishbone layout warehouses under the class-based storage strategy. The fishbone layout was divided into three storage areas for class A, class B, and class C items according to the proportion using the straight line, to meet the classification requirements of items. Under the class-based storage strategy, to evaluate the performance of the return routing strategy and the S-shape routing strategy, the stochastic models of the expected walking distance of the two routing strategies in the fishbone layout warehouse are established by calculating the sum of the expected walking distances in diagonal cross-aisles and picking aisles. Finally, the stochastic models of the two routing strategies are simulated and verified, and the impacts of the two routing strategies on walking distances are analyzed by comparing the expected distances under different ordering frequencies and space allocation strategies. The numerical results show that the return routing strategy has an advantage over the S-shape routing strategy when determining the relevant parameters of the fishbone layout and picking orders. Meanwhile, it also provides a theoretical basis for research on stochastic models of routing strategies in fishbone layout warehouses under the class-based storage strategy.

The routing strategy for order picking is an important factor in the efficiency of warehouse picking, and improvements to the warehouse layout provide more routing options for picking. The number of storage locations to be visited during the picking operation also has an impact on the selection of routing strategies. In order to achieve an effective improvement in the efficiency of picking operations in warehouse distribution centers, this paper focuses on the leaf warehouse layout based on the previous single-command operation strategy and extends it to study the multi-command operation strategy, in which three heuristic routing strategies, the S-shape, the return, and the composite, are introduced to solve the walking distance problem of picking operations, with the study of the selection of the routing strategy for different numbers of storage locations to be visited. Based on the distance equation between any two storage locations to be visited in the leaf layout warehouse, travel distance models corresponding to the three routing strategies in the picking operation are constructed, and the cuckoo search algorithm is introduced to solve and calculate the travel distance of the composite strategies for the experiments. In addition, the computational experiments of the three path strategies are carried out according to the different numbers of storage locations to be visited in the picking operation. By analyzing the numerical results, we find that the composite strategy has the best overall results among the three routing strategies, with the average values of optimization rates exceeding 30% (the S-shape) and 40% (the return), respectively. At the same time, the return strategy outperforms the S-shape strategy when the number of locations to be visited is less than seven. As the number of locations to be visited increases, the S-shape strategy gradually outperforms the return strategy. From a managerial and practical perspective, compared to the single-command operation strategy that is the focus of the current research, the multi-command operation strategy we studied is more relevant to the actual situation of order merging picking in warehouses and can effectively improve the efficiency of picking operations, the competitiveness of enterprises, and customer satisfaction of e-commerce enterprises.

Aiming at the multibox 3D packing problem of heterogeneous extrudable items in e-commerce retail department stores, the optimization goal is to select appropriate packaging materials for packing all items in the order. On this basis, the number of packaging materials used is the least and the space utilization rate is high. A heuristic algorithm is designed. Firstly, the items are sorted in descending order according to volume, and then the items are boxed according to the rule of “layer generation.” In order to verify the feasibility and effectiveness of the algorithm, the data provided by a large domestic e-commerce platform are used to analyse and compare the space utilization of packaging materials under the conditions of no extrusion operation and extrusion operation. The feasibility and effectiveness of the algorithm in the packaging and delivery link in the storage field of e-commerce retail department stores are proved.

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