In China, the transportation sector contributes about 18% of the total carbon emissions. This research contributes to measuring the energy and carbon emission efficiency (ECEE) of regional transportation systems (RTS) in China considering uncertain carbon emissions. A radial chance-constrained data envelopment analysis (DEA) model is developed to estimate the overall efficiency, and a nonradial chance-constrained DEA model is presented to evaluate the pure energy efficiency (PEE) and the pure carbon emission efficiency (PCEE). We prove that the proposed chance-constrained DEA models can effectively address the uncertain carbon emissions when measuring efficiency. We find that most of China’s RTS have low ECEE and the inefficiencies are mainly due to the lower gasoline utilization efficiency and the lower kerosene utilization efficiency. In addition, east China performs better than central China, and central China performs better than west China. In China, the unbalanced regional development of the ECEE in transportation corresponds with the unbalanced regional economic development. We provide some valuable suggestions based on the evaluation of the potential cuts in each kind of energy and the potential decreases in carbon emissions.

Pallets are widely used around the world. Pallet pooling, as a useful management method of pallets, has become more and more popular. It is very important to allocate pallets over a pallet pool efficiently. However, there is very little literature on the pallet allocation problem as to our knowledge. This article addresses a pallet allocation problem where some uncertain parameters can be estimated through historical data, while some others cannot be. To address this problem, with the method of stochastic chance constrained programming and scenario planning, we propose an optimization model in which sustainable factors and customer priority factors are taken into account. The sustainable factors are used to measure the sustainable development costs of pallets. The customer priority factors are used to measure the customers’ rating. It is proved by experimental tests that the model can help pallet pool managers make more effective pallet allocation schemes against uncertainty. It is also suggested by the results that we should pay attention to sustainable factors and customer priority factors when making decisions.

In a pallet pool, pallets would be delivered through a supply chain. The operation procedure that consists of at least five operation processes as distribution, reposition, recycling, purchase (or rent), and maintenance is quite complex. These pallets are likely to be damaged, lost, destroyed, and so on. So, it is necessary to monitor the pallets using radio-frequency identification technology. However, there is no literature on the management of a pallet pool with both radio-frequency identification–tagged pallets and non-tagged pallets being put into consideration. In our research, an optimization model is presented to manage such a pallet pool. The objective of the optimization model is to minimize the total operation cost of a pallet pool including distribution cost, reposition cost, recycling cost, purchase or rent cost, loss cost, maintenance cost, loading and unloading cost, storage cost, and punishment cost. A particle swarm optimization algorithm is developed in Microsoft Visual Basic. Our numerical example shows that the optimization model and particle swarm optimization algorithm are effective. It is proved that the model and algorithm also can be used to measure whether the investment of a radio-frequency identification system is valuable or not. We proposed some suggestions for the pallet pools management.

Cold chain logistics has been playing a more and more crucial role in modern society. As a special professional cold chain logistics, emergency cold chain logistics can provide quality assurance for temperature-sensitive products in emergency situations. Due to the fact that demand is uncertain in emergency situations, the cold chain logistics companies have to deal with the issue of uncertainty. However, there is no literature on the emergency cold chain logistics distribution optimization problem with uncertain demand. This research contributes to solving this problem. To deal with uncertain demand in emergency situations, an emergency cold chain logistics distribution optimization model with time windows is proposed based on scenario analysis. The objectives of the model are to minimize the total cost and shorten the delivery time simultaneously. The model can also optimize product procurement and refrigerated vehicle renting. The multi-scenario optimization model is applied to a Chinese cold chain logistics center to verify its effectiveness.

In the production of supply chains, dual-role factors and undesirable outputs are commonly encountered. However, current research fails to effectively address these factors, leading to inaccurate assessments of efficiency. To address these limitations, this study proposes a method called the network slacks-based measure considering both dual-role factors and undesirable outputs. Our methodology treats dual-role factors as strongly disposable and employs 0–1 programming to manage these factors, while utilizing the slacks-based approach to handle undesirable outputs. Data from 10 automotive supply chains are collected to validate the effectiveness of the proposed method. To examine the impact of intermediate products, we compare their efficiency under different link activities. The findings suggest that using fixed links to manage intermediate products may overestimate production efficiency. Furthermore, the impact of dual-role factors is evaluated under two scenarios: weak disposability and the exclusion of dual-role factors. The results demonstrate that treating dual-role factors as weakly disposable may overestimate efficiency, whereas ignoring them may lead to an underestimation of efficiency.

Development of sharing economy has brought new opportunities to the development of green logistics. Pallet pooling is a typical type of sharing economy. It has been recently promoted in almost every country in the world. Researchers have reached a common agreement that establishing an effective pallet pool is of great importance to the pallets use efficiency. It is also believed that the implementation of pallet pool will substantially contribute to the economic and social development. Detailed analysis of pallet pooling such as benefit analysis, mode choose, pallet allocation model & algorithm, quality control, etc. are discussed in this paper. Based on literature review, several important problems are listed for future study. These problems are information management, supply chain management, rental pricing, pallets tracking and allocation, quality control, sustainable development (carbon emissions), and “internet plus pallet pooling”. Some suggestions on China’s pallet pooling development are proposed as well.