The concept of sustainable development requires us to explore a completeness model of low carbon transport and service in the light of the advancement of changes in world cooperation policy. Various kinds of carbon constraints not only limit emissions of contaminants from E-commerce Enterprise of different countries, but they also ensure the market activity around the Belt and Road, so as to avoid the implementation reducing the company’s profits significantly. This paper discusses of the strictest periodic low-carbon constraints_(PLC) and the expansion of the mainstream with three relatively weak attributes—cumulative_(CLC), full cycle_(FCLC), and volatility_(VLC)—taking into account the offline delivery of lead time and the online relationship between supply and demand on the platform. We have established four decision models with different carbon confinement intensities and inferred the impact of more detailed carbon constraints on E-commerce delivery strategies. The appropriate operational decisions, under a wide spectrum of carbon constraints, help e-companies develop scientific delivery plans, and provide some inspiration for the promotion of low carbon economy system construction and environmental significance.

A vehicle‐commodity matching problem (VCMP) is presented for service providers to reduce the cost of the logistics system. The vehicle classification model is built as a Gaussian mixture model (GMM), and the expectation‐maximization (EM) algorithm is designed to solve the parameter estimation of GMM. A nonlinear mixed‐integer programming model is constructed to minimize the total cost of VCMP. The matching process between vehicle and commodity is realized by GMM‐EM, as a preprocessing of the solution. The design of the vehicle‐commodity matching platform for VCMP is designed to reduce and eliminate the information asymmetry between supply and demand so that the order allocation can work at the right time and the right place and use the optimal solution of vehicle‐commodity matching. Furthermore, the numerical experiment of an e‐commerce supply chain proves that a hybrid evolutionary algorithm (HEA) is superior to the traditional method, which provides a decision‐making reference for e‐commerce VCMP.

A production department and two distribution departments form a multimodal logistics supply network. The production department provides two ordering opportunities within one production cycle, and the real-time updates of demand information are required in the interval between two orders. Based on this, the paper studies the security inventory optimization problem of multimodal transport networks. On the basis of portraying the real-time information update process, the multimodal network optimization model without considering safety stock and the multimodal network optimization model considering safety stock are constructed, respectively, and the transshipment price and demand information of the intermodal network are updated. The parameters are analyzed for sensitivity. The analysis of examples shows that, on the one hand, with the update of demand information, the distribution department adopts the multimodal transport model with safety stock to improve the profit of the distribution department and the supply network. On the other hand, the production sector can meet market demand with a lower production scale, while the distribution department can effectively respond to stochastic demand through a multimodal model with safety stock.

The accumulation of real‐time data has attracted the attention of various industries because valuable information can be extracted from the effective model and method design. This paper designs a low‐carbon model and focuses on the real‐time information‐sharing network in order to get sustainable strategies promptly and exactly. The design problem is concerned with determining optimal integration strategies on a series of multilocation, multipath, and multiwarehouse freight provided by an information‐sharing network to find an effective balance between the total costs and carbon emission. Firstly, the biobjective information‐sharing network model is established to describe real‐time problem with total cost and carbon emission factor. Secondly, a double‐layer bacterial foraging algorithm is divided into inner and outer layers to solve the model, in which the inner section solves the transportation and inventory problems, and the outer section solves the supplier location problem. The double‐layer bacterial foraging algorithm realizes the optimization of multisource e‐commerce information‐sharing model through nesting inside and outside layers. Finally, double‐layer bacterial foraging algorithm can be confirmed to get the global optimal solution rapidly based on test data and the e‐business case study of Jingdong, China.

For the traditional last-kilometer delivery, commodities are sent from the distribution center to the distribution transfer station, which are then delivered by the couriers from the distribution transfer station to the consumers. This single distribution channel cannot prioritize services for consumers closer to the distribution center, resulting in a waste of distribution resources. To deal with the last-kilometer delivery problem, this paper attempts to build a dual-channel distribution system consisting of UAVs and couriers. And the impact of the market allocation proportion on the expected profit of the last mile service through the two different distribution channels is discussed and analyzed. It is proved that the improved revenue sharing contract can realize the coordination of the dual-channel distribution between UAVs and the couriers. The numerical examples verify the effectiveness of the model and contract coordination. According to the research, first, with the increase in the uncertainties of the delivery quantity, the profit of the UAV channel shows a downward trend, while the profit of the courier channel remains basically the same. This is because the labor cost of the courier channel is relatively stable. Second, with the increase in the market allocation proportion of the last-kilometer delivery, the optimal delivery quantity of the UAV channel and the optimal order quantity of the courier channel are both increasing, while the overall profit of the last-kilometer is first rising and then decreasing. Third, the expected profit of the UAV channel and the courier channel can achieve Pareto improvement through the improved revenue sharing contract.