Smart ports represent the current trend of port development. Intelligent operations reduce the daily production cost of ports, facilitate efficient production, strengthen the risk mitigation ability and comply with the requirements for long-term development. However, a systematic and scientific smart port evaluation method is missing to nail down the evaluation indicators of a smart port and enable accurate evaluation of a port’s degree of intelligence. This paper analyzes the concept of the smart port, establishes a set of smart port evaluation indicator systems, and applies a single-valued neutrosophic exponential similarity measure to port evaluation to enable quantitative evaluation of port integrity. This evaluation method is capable of decision-making in the event of incomplete, uncertain, and inconsistent information during general evaluation, opening up a new method for smart port evaluation, and acting as a helpful tool for ports to carry out improvements during actual application.

When vessels are docked at ports, traditional auxiliary engines produce substantial pollutants and noise, exerting pressure on the port environment. Shore power technology, as a green, energy-efficient, and emission-reducing solution, can effectively mitigate ship emissions. However, its widespread adoption is hindered by challenges such as high costs, compatibility issues, and connection complexity. This study develops a multi-objective optimization model for the coordinated allocation of shore power and berth scheduling, integrating economic benefits, environmental benefits, and operational efficiency. The NSGA-III algorithm is employed to solve the model and generate a Pareto-optimal solution set, with the final optimal solution identified using the TOPSIS method. The results demonstrate that the optimized shore power distribution and berth scheduling strategy can significantly reduce ship emissions and port operating costs while enhancing overall port resource utilization efficiency. Additionally, an economically feasible shore power allocation scheme, based on 80% of berth capacity, is proposed. By accounting for variations in ship types, this study provides more targeted and practical optimization strategies. These findings offer valuable decision support for port management and contribute to the intelligent and sustainable development of green ports.

Port throughput, as an indicator reflecting port scale, is associated with the port–city’s population base. By establishing an allometric growth model between the two, we can well verify the delicate relationship between port throughput and urban population. This article takes the throughput of Shanghai port and the population of Shanghai city as an example and studies the relative growth rate ratio between the two, that is, the scaling exponent b. In this example, the exponent b = 0.58 which is smaller than the theoretical value of 0.85, suggesting the improper development relationship between the two for the current phase. Shanghai urban population tends to be saturated, with the growth rate slowing down, and the contribution of urban population to port throughput decreasing. If this development trend proceeds for long, Shanghai port growth scale will be severely restricted. Apart from quantitative research on the relationship between the development rates of Shanghai port throughput and Shanghai urban population, this article also uses the Logistic model to forecast Shanghai port throughput and Shanghai urban population in the future to develop a scientific plan for Shanghai port scale so that port and city can achieve coordinated development.

In this paper, the dual hesitant fuzzy rough set (DHFRS) is studied from the viewpoint of assessment deviations. Firstly, according to the relationship between intuitionistic fuzzy set and vague set, the DHFRS is transferred into a fuzzy set, where the membership of any given element to it has multi-grouped values. By the idea of bootstrap sampling, a group of four sets are generated to describe the membership degree on DHFRS, where the elements of the aforementioned sets are all considered as assessment values. Secondly, the generated sets are dealt with by assessment deviation theories, and specifically, two variables are proposed to describe the systematic and random deviations of the sets. Thirdly, the true-value of the membership degree of any elements to the set is estimated by a deviation-based dual hesitant fuzzy rough weighted aggregating operator. Fourthly, a dual hesitant fuzzy rough pattern recognition approach based on assessment deviation theories is proposed. Finally, an urban traffic modes recognition example is given to illustrate the validity of the proposed theories on DHFRSs.

When build–operate–transfer (BOT) roads are transferred back to the government upon the expiry of their contract, they are typically considered to be public roads and are no longer subject to tolls. However, in China, BOT roads, after being transferred to the government, remain tolled by the government in order to maintain efficiency. Therefore, such roads are termed public toll roads (PTRs). During the operational phase of PTRs, ongoing operating costs become a significant financial burden compared to the initial investment made for their construction. Against the backdrop of global carbon emission efforts, this paper studies the operational strategy of PTRs in terms of car emission costs, which constitute a portion of PTRs’ operation costs. This paper explores the operational strategy of PTRs, including whether the government should operate the road independently or outsource their operation to a competent private firm. Our analysis concludes that the operator should manage PTRs for the entire duration of their operation by maintaining self-financing while also accounting for operation costs. In this study, governmental regulations for the cost of carbon emissions are also studied.