Optimizing e-commerce warehousing through open dimension management in a three-dimensional bin packing system.

In the field of e-commerce warehousing, maximizing the utilization of packing bins is a fundamental goal for all major logistics enterprises. However, determining the appropriate size of packing bins poses a practical challenge for many logistics companies. Given the limited research on the open-size 3D bin packing problem as well as the high complexity and lengthy computation time of existing models, this study focuses on optimizing multiple-bin sizes within the e-commerce context. Building upon existing research, we propose a hybrid integer programming model, denoted as the three dimensional multiple option dimensional rectangular packing problem (3D-MODRPP), to address the multiple-bin size 3D bin packing problem. Additionally, we leverage well-established hardware and software technologies to propose a 3D bin packing system capable of accommodating multiple bin types with open dimensions. To reduce the complexity of the model and the number of constraints, we introduce a novel assumption method for 0-1 integer variables in the overlap and rotation constraints. By applying this approach, we significantly streamline the computational complexity associated with the model calculations. Furthermore, we refine the dataset by developing a customized version based on the classical Three-Dimensional One-Size Dependent Rectangular Packing Problem (3D-ODRPP) dataset, leading to improved outcomes. Through comprehensive analysis of the research results, our model exhibits remarkable advancements in addressing the strong heterogeneous bin packing problem, the weak heterogeneous bin packing problem, the actual bin packing problem, and the bin packing problem with multiple bin types and open sizes. Specifically, it significantly reduces model complexity and computation time and increases space utilization. The system designed in this study paves the way for practical applications based on the proposed model, providing researchers with broader research prospects and directions to expand the scope of investigation in the field of 3D bin packing. Consequently, this system contributes to solving complex 3D packing problems, reducing space waste, and enhancing transportation efficiency.

Stochastic models of routing strategies under the class-based storage policy in fishbone layout warehouses.

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.

Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse.

The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse.

Expression of porcine respiratory and reproductive syndrome virus membrane-associated proteins in Listeria ivanovii via a genome site-specific integration and expression system.

Listeria ivanovii (LI) possesses a facultative intracellular life cycle in macrophages and non-professional phagocytes thus making it a potential novel vaccine vector. We have developed a genome site-specific integration system as a universal tool for constructing the live LI-based vaccines. Using this system, the porcine reproductive and respiratory syndrome virus (PRRSV) orf5 and orf6 genes, coding for PRRSV membrane-associated protein GP5 and M, respectively, were integrated into the LI genome. Genome PCR and sequencing results showed that the orf5 or orf6 gene had been integrated into the LI genome downstream of orfXYZ or mpl gene. Western blot analysis of the non-secreted and secreted bacterial protein samples showed the expression and secretion of GP5 or M protein from the recombinant LI strains. The secretion of the heterologous proteins is a key step for bacterial vaccine vectors to deliver the antigens to the immune system to stimulate antigen-specific immune responses. Therefore, this integration system may be a potential tool for constructing novel vaccines using live LI as vector.

Long-term exposure to decabrominated diphenyl ether impairs CD8 T-cell function in adult mice.

Polybrominated diphenyl ethers (PBDEs) are ubiquitous environmental pollutants that accumulate to high levels in human populations that are subject to occupational or regional industry exposure. PBDEs have been shown to affect human neuronal, endocrine and reproductive systems, but their effect on the immune system is not well understood. In this study, experimental adult mice were intragastrically administered 2,2',3,3',4,4',5,5',6,6'-decabromodiphenyl ether (BDE-209) at doses of 8, 80 or 800 mg/kg of body weight (bw) at 2-day intervals. Our results showed that continuous exposure to BDE-209 resulted in high levels of BDE-209 in the plasma that approached the levels found in people who work in professions with high risks of PDBE exposure. Reduced leukocytes, decreased cytokine (IFN-γ, IL-2 and TNF-α) production and lower CD8 T-cell proliferation were observed in the mice exposed to BDE-209. Additionally, mice with long-term BDE-209 exposure had lower numbers of antigen-specific CD8 T cells after immunization with recombinant Listeria monocytogenes expressing ovalbumin (rLm-OVA) and the OVA-specific CD8 T cells had reduced functionality. Taken together, our study demonstrates that continuous BDE-209 exposure causes adverse effects on the number and functionality of immune cells in adult mice.