Search Results (124)

In fourth-generation district heating systems (DHSs), the supply temperature of modern heat sources such as heat pumps and waste heat can potentially be reduced by mixing in hot water from combustion-based producers, thereby increasing efficiency and facilitating integration into networks with unrenovated buildings. However, this approach introduces the risk of thermo-hydraulic oscillations driven by mixing dynamics, transport delays, and mass flow adjustments by consumers. These oscillations can increase wear and cost and may potentially lead to system failure. This study addresses the asymptotic stability of multi-supplier DHSs by combining theoretical analysis and practical validation. Through linearization and Laplace transformation, we derive the transfer function of a system with two suppliers. Using pole-zero analysis, we show that transport delay can cause instability. We identify a new control law, demonstrating that persisting oscillations depend on network temperatures and low thermal inertia and enabling stabilization through careful temperature selection, thorough choice of the slack supplier, or installation of buffer tanks. We validate our findings using dynamic simulations of a nonlinear delayed system in Modelica, highlighting the applicability of such systems to real-world DHSs. These results provide actionable insights for designing robust DHSs and mitigating challenges in multi-supplier configurations by relying on thoughtful system design rather than complex control strategies. Full article

This paper considers the single-machine scheduling problem of total tardiness minimization. Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. The advent of Deep Q-Networks (DQNs) within the reinforcement learning paradigm could be a viable approach to transcending these limitations, offering a robust and adaptive approach. This study introduces a novel approach utilizing DQNs to model the complexities of job scheduling for minimizing tardiness through an informed selection utilizing look-ahead mechanisms of actions within a defined state space. The framework incorporates seven distinct reward-shaping strategies, among which the Minimum Estimated Future Tardiness strategy notably enhances the DQN model’s performance. Specifically, it achieves an average improvement of 14.33% over Earliest Due Date (EDD), 11.90% over Shortest Processing Time (SPT), 17.65% over Least Slack First (LSF), and 8.86% over Apparent Tardiness Cost (ATC). Conversely, the Number of Delayed Jobs strategy secures an average improvement of 11.56% over EDD, 9.10% over SPT, 15.01% over LSF, and 5.99% over ATC, all while requiring minimal computational resources. The results of a computational study demonstrate DQN’s impressive performance compared to traditional heuristics. This underscores the capacity of advanced machine learning techniques to improve industrial scheduling processes, potentially leading to decent operational efficiency. Full article

The objective of this work is to analyze the relevance of governance (corporate and ownership concentration) for the divisional inter-temporal dynamic efficiency in piped natural gas utilities in Brazil. The main innovative contribution of this work is the application of inter-temporal (dynamic) efficiency analysis with network structure in the first stage, in this case, the ‘Dynamic DEA (Data Envelopment Analysis) with network structure: A slacks-based–DNSBM (Dynamic Network Slacks-Based Measure)’, in which two divisional interactions ${\delta }_{ok}^{\ast }$ (technical–operational and economic–financial division) between ${\tau }_o^{t\ast }$ periods and divisional ${\rho }_{ok}^{t\ast }$ periods are reflected in the overall efficiency scores ${\theta }_o^{\ast }$, representing an approach not yet explored by the previous literature on the sector and subject investigated. The database used corresponds to 21 Brazilian natural gas utilities in the form of a balanced data panel, which were collected for the period 2014–2019. The second stage (explanatory) was estimated through the panel with random effects to identify the relationship between governance and efficiency, considering certain context factors. The results show that the average general efficiency was 74.96%, resulting from the interactions between the average efficiency rates of 72.21% of the technical–operational division and 82.03% of the economic–financial division, and suggest that the corporate governance index and ownership (public or private) are not relevant factors for the efficiency results studied. Full article

Floating offshore wind turbines (FOWTs) are severely restricted in numerous sea areas due to challenges from the strong nonlinear characteristics of mooring chains in shallow water (less than 50 m). Therefore, this paper introduces a design method of mooring chains of a FOWT at a water depth of 44 m and carries out a parametric sensitivity analysis on length, nominal diameter, and clump weights of mooring chains. The results of the study found that compared with the mooring chains in deep water, the mooring chains in shallow water show obvious nonlinear characteristics in mooring tension, the lying section of the mooring chain on the seabed, and the mooring chain spatial angle, which brings great risk to the safe operation of FOWTs. The change in the nominal diameter of the mooring chain has a certain impact on the dynamic characteristics of a FOWT, but it is not as significant as that from the change in the length of the mooring chain. In addition, a mooring chain in shallow water is prone to the slack–taut phenomenon; thus, this paper puts forward an optimization investigation using clump weights at the suspension section of the mooring chain, which improved the performance of the mooring chain significantly. Full article

Sustainable tourism entails balancing economic growth, environmental protection, and energy utilisation. However, the current interactive dynamics between urban agglomeration tourism systems and the energy–economy–environment (EEE) system, as well as the sustainable efficiency of the tourism–energy–economy–environment (TEEE) system, remain unclear. For the first time, this study employs a super-efficiency network slacks-based measure (SE-NSBM) model to interact with tourism and EEE systems, proposing a novel network structure that includes feedback variables. To validate the proposed model, this study evaluated the efficiency of the TEEE system and its subsystems in the Yangtze River Delta urban agglomeration (YRDUA) from 2016 to 2020. The study revealed significant variations in the efficiency of the TEEE, tourism, and EEE systems among cities in the YRDUA, with a discernible downward trend. The TEEE and tourism systems exhibit relatively weak coping capabilities when faced with significant unforeseen events, highlighting the urgent need to strengthen system resilience. The results also demonstrate that the new model effectively resolves the issue of efficiency overestimation in the TEEE system observed in traditional models, which tend to overestimate actual efficiency by 3%. The novel model and empirical results offer decision-makers new perspectives and practical insights into formulating sustainable tourism policies. Full article

This paper investigated the tracking problem of mixed ${\mathcal{H}}_{\infty }$ and $L_2-L_{\infty }$ adaptive fault-tolerant control (FTC) for continuous-time interval type-2 fuzzy systems (IT2FSs). For the membership function mismatch and uncertainty between the modules of the nonlinear system, the IT2 fuzzy model is applied to linearly approximate it. The observer can sensitively estimate the system state, and the adaptive fault estimation functions can estimate adaptively the fault signals, which enables the designed adaptive FTC scheme to ensure the asymptotic stability of the closed-loop control system and achieve the desired mixed ${\mathcal{H}}_{\infty }$ and $L_2-L_{\infty }$ tracking performance. The designed adaptive control law can achieve the purpose of dynamic compensation for faults and disturbances, and the introduced lemmas further reduce the design conservatism by adjusting the slack parameters and matrices. Finally, a mass-spring-damping system is used to illustrate the effectiveness of the designed method. Full article

Taiwan is currently an aging society and will be a super-aging society in the near future. The purpose of this research is to use two models of data envelopment analysis (DEA)—the slacks-based measurement (SBM) model and the dynamic slacks-based measurement (DSBM) model—to analyze the efficiency of long-term care (LTC) in Taiwan. This analysis aims to explore the current situation of LTC in Taiwan and provide policy recommendations for LTC. The computation empirical result on the LTC efficiency score presents that the DSBM model exhibits higher efficiency than the SBM model after considering the carry-over variable in the former model. The result from the SBM model indicates that Taiwan’s outlying islands display the worst LTC efficiency, but this result does not appear in the DSBM model. Lastly, these two models both indicate that the number of elderly people being serviced in institutions exhibits higher efficiency and lower slack than those serviced in homes in 2017 and 2018. This paper concludes that the DEA approach is a viable method for examining the performance of the LTC services system as Taiwan approaches a super-aged society. Full article

This paper presents a mathematical approach to analyzing carbon abatement costs and the allocation of carbon emission allowances in China’s industrial sectors. We utilize input–output data from 30 Chinese provinces between 2009 and 2018 to estimate carbon abatement costs by applying the slack-based measure (SBM) efficiency model and its dual form. The SBM model captures inefficiencies and offers a rigorous framework for measuring abatement costs. Using these costs, we develop a centralized allocation data envelopment analysis (DEA) model, which maximizes sectoral benefits through optimal reallocation. This DEA model is formalized as a linear programming problem, with the aim of determining the efficient allocations of carbon allowances while maintaining the system’s economic productivity. Furthermore, we construct intertemporal, interregional, and spatiotemporal allocation DEA models to examine the dynamics of carbon emission allowance allocation over time, space, and combined spatiotemporal dimensions. These models offer insights into the efficiency of carbon markets under varying conditions. Our proposed new mathematical formulations reveal optimal allocation strategies that can balance emission reductions with industrial productivity. This study also provides novel mathematical frameworks for analyzing the carbon allowance distribution and contributions to both the theory and application of mathematical optimization in environmental policy design. Our findings reveal that China’s industrial carbon abatement costs exhibit significant interprovincial and regional differences. Developed provinces with higher levels of industrial development have higher carbon abatement costs, while provinces with less-developed industrial sectors have lower costs. Under the interregional allocation scenario of carbon emission allowances that consider abatement costs, developed provinces have smaller industrial carbon emission reductions, whereas less-developed provinces have larger reductions. In the intertemporal allocation scenario, provinces with larger industrial economies face greater emission reduction tasks. Under the combined interregional and intertemporal allocation scenario, industrial sectors in coastal developed provinces have lower carbon emission reductions, while those in inland less-developed provinces have higher reductions, mirroring the spatial allocation results of carbon emission allowances. Full article

This study investigates the dynamic behavior of a three-body tethered satellite system with a flexible tether, focusing on a scenario in which a payload is transported along the tether connecting two satellites. Traditional models use rigid tethers, limiting the analysis of complex dynamics such as tether deformation, slack, and rebound. To address these limitations, we employed the absolute nodal coordinate formulation (ANCF) to model the flexibility of the tether. We derived nonlinear equations of motion using Lagrange’s equation and solved them using the Newmark time integration method to obtain the dynamic responses of the satellite system. Our findings revealed that the Coriolis effect caused significant deviations in the payload trajectory as its mass and speed increased, leading to greater tether deformation and slack, and potential system destabilization. Additionally, axial force fluctuations in the tether varied notably as the payload moved, transitioning between tensile and compressive states. This study provides a more accurate representation of three-body tethered satellite systems by incorporating tether flexibility, offering valuable insights into the dynamic behavior and stability of the system. Full article

Hydropower is a significant component of China’s contemporary energy framework, with its construction and operation critically contributing to the advancement of sustainable development in the region. However, the influence of hydropower development on regional sustainable development is not evident, and the course of its effect is not clear. In this work, on the basis of assessing the effect of hydropower development on regional sustainable development, a system dynamics (SD) simulation model was created, and 15 distinct development modes were set and tested. The relative driving efficiency of hydropower growth on sustainable development in a province in Southwest China under several scenarios was assessed using the super-efficiency-slacks-based measurement (Super-SBM), and an efficiency analysis was undertaken. The study’s findings demonstrate that: (1) Hydropower development had a complex driving influence on sustainable development in the province in 2015–2022. (2) The relative driving efficiency of the province over the study period exhibited a changing pattern and was at a high level greater than 0.7. (3) New hydropower investment and hydropower generation are the major factors impacting the relative driving efficiency of hydropower development on regional sustainable development in the province. The study’s findings provide a platform and reference for supporting regional sustainable development through hydropower development. Full article

Due to the continuous growth of global energy demand and the urgent pursuit of sustainable development goals, renewable energy development has become a vital strategy to deal with energy challenges and environmental issues. Renewable energy generation efficiency (REGE) around the world has begun to be examined, and ambitious goals with a sense of mission within a predetermined timeline have been set. The goal of this paper is to use the dynamic slacks-based measure (DSBM) data envelopment analysis (DEA) method to obtain the REGE for 44 Asian economies from 2010 to 2021. This paper also uses Tobit regression analysis to explore the factors that may affect the REGE. The empirical results indicate that the REGE in 17 economies reached the efficiency target during this period. When classified by income level, differences in average REGE are observed among high-income, upper-middle-income, lower-middle-income, and low-income economies. Additionally, differences in average REGE exist between tropical and temperate economies when classified by geographic latitude. Furthermore, through the Tobit regression model, we determine that information digitalization, financial openness, technological innovation ability, and renewable energy device capacity share all have significant positive effects on REGE, but life quality and democracy degree have significant negative impacts on REGE. Moreover, it has been found that the REGE scores of Asian economies exhibit a status similar to the middle-income trap. The outcome of the research provides Asian governments and those middle-income economies with ways to enhance REGE. Due to data limitations, this study cannot estimate the convergent solution based on the data of the research sample, and a new advanced Panel Tobit model is required. Full article

In this study, the static and dynamic performance efficiencies of container terminals are analyzed and compared for the main container terminals in China and Korea. The static performance efficiency is calculated using the Super-SBM model based on slack variables at the micro-level. An analysis on the dynamic performance efficiency is conducted with the Malmquist index method. The factors of scale and technology of container terminals are mainly taken into account to explore the performance efficient improvement path of container ports. We obtained the following conclusions: (1) The container terminals in Korea show a similar performance efficiency level to the terminals in China, and their performance efficiency is an overall upward trend over the past five years. (2) The main reason for inefficiency in the container terminals in China and Korea is predominantly scale inefficiency. (3) Boosting the automation degree does not have a completely positive impact on the efficiency of the terminal. (4) In 2019–2023, the technical progress index of all container terminals in China and Korea showed a decreasing trend, leading to performance inefficiency of the container terminals. Full article

This study analyzed the relevance of governance structure for efficient revenue collection by Brazilian water utilities (WUs). Data were collected from the National Information System on Sanitation (SNIS) for 127 Brazilian WUs, covering a balanced longitudinal panel from 2018 to 2022. The governance structures evaluated included ownership (public or private) and corporatization (publicly traded or not). We searched scientific databases and did not find any studies on the efficiency of specific WUs in collecting customer bills for services rendered and its relationship with this type of governance; thus, this is the main innovative contribution of this study to the literature. In the first stage, this study utilized the dynamic slack-based model (DSBM) to assess revenue collection efficiency. In the second stage, an econometric model with generalized estimating equation (GEE) was used to explain the efficiency. The findings revealed a global average inefficiency in revenue collection of 50.47%. Corporatization was linked to higher collection efficiencies, while ownership type was significantly linked with lower collection efficiency. Factors such as tariff accessibility, urbanization, and the COVID-19 pandemic also influenced efficiency. This study suggests that regulatory bodies should consider these insights to implement policies that prevent inefficiencies from affecting the tariff system for services. Full article

Against the backdrop of climate change and the “dual carbon” goals, enhancing the ecological efficiency of cryospheric tourism is crucial not only for the high-quality development of the tourism industry itself but also for the protection of the ecological environment and the promotion of green sustainable development in the cryospheric region. In light of this, this study, taking climate change as its background and based on the perspective of carbon emission constraints, integrates multidimensional factors such as “climate change, carbon emission constraints, and cryospheric resources” into a unified measurement framework to construct a model for evaluating the ecological efficiency of tourism in the cryosphere. Specifically, the model considers inputs, expected outputs, and unexpected outputs. Subsequently, employing the super-efficiency slack-based measure (SBM) model, this study measures the tourism ecological efficiency (TEE) of three provinces (Xinjiang, Qinghai, Tibet) in the cryosphere from 2013 to 2021 and utilizes the Malmquist–Luenberger index and gray correlation model to reveal their dynamic changes, efficiency decomposition, and influencing factors. The results indicate that: (1) The overall mean of TEE in the cryosphere is between 0.2428 and 1.2142, Over the study period, the average annual growth rate and corresponding confidence interval were 14.74%, (−8.61%, 64.23%), showing a significant fluctuating growth trend. Among them, Xinjiang stands out, with its mean scores ranging from 0.2418 to 1.6229, surpassing the overall average level of the cryosphere. (2) During the study period, the overall dynamic efficiency of tourism ecology in the cryosphere increased by 21.54%, driven by the synergy of technological progress (TC), pure technical efficiency (PET), and scale efficiency (SE). For each province, the dynamic efficiency of tourism ecology has improved, but to varying degrees. (3) Regarding the driving factors of TEE in the cryosphere, each driving factor is closely related to TEE, ranked from large to small as follows: carbon emission structure, level of economic development, infrastructure, intensity of technological input, industrial structure, resource endowment, and environmental regulation. This article holds theoretical and practical significance for promoting the high-quality development of polar tourism and achieving synergistic progress between the economy and environment. Full article

As main components of terrestrial ecosystems, forests play irreplaceable roles in maintaining ecological balance and protecting the basic environment for human survival and development. In this study, the dynamic changes in the forest landscape connectivity in Zhejiang province in 2000, 2010, and 2020 were detected by identifying ecological sources and evaluating connectivity indexes based on morphological spatial analysis (MSPA) and a minimum cumulative resistance (MCR) model. The results are as follows: (1) The forest area of Zhejiang increased by 64.88% from 2000 to 2020, indicating that the overall habitat quality has improved and that ecological risks have decreased, which are attributed to Zhejiang’s adherence to comprehensive environmental management. (2) Regions with low connectivity are distributed mainly in the north, where human activities are intensive. The overall pattern of high connectivity in the middle of the region and low connectivity elsewhere demonstrates the uneven distribution of forest landscape connectivity across the province. (3) The extracted ecological corridors have a mesh-like structure that is dense in the middle and slack in the north. Important corridors have disappeared over time, indicating potential issues in maintaining connectivity for species migration. (4) These results can provide optimization strategies for ecological infrastructure planning in Zhejiang province and offer a theoretical reference for the optimization of the ecological network system. Full article