Sustainable Network Research Articles

A sustainable and resilient humanitarian relief chain network design for distributing assembled relief items dynamically considering perishability, under disruption

Purpose Due to mitigate against natural disasters like earthquake and to distribute relief items, designing humanitarian relief chain networks is an attentional issue. Agile and efficient distribution of relief items after occurring a disaster is significant, especially when some of the relief items are perishable. Therefore, the purpose of this paper is to create a resilient and integrated decision-making structure to distribute relief items at demand points, considering two dimensions of sustainability, under disruption. Design/methodology/approach This study developed a mixed-integer nonlinear mathematical model to handle the pre- and post-disaster planning when a disaster occurs. The represented model has two objective functions: minimizing weighted unmet demand and total costs. Therefore, to convert this multi-objective problem into a single objective one, the e-constraint method was applied. Findings The main results showed that considering some resilience strategies has a significant effect in reducing the weighted amount of unmet demand and saves the total costs. More precisely, considering resilience strategies results in a 60% reduction in total unmet demand and 11% reduction in total pre-positioning costs. On the other hand, reducing the maximum response time with applying resilience strategies is another achievement of the present study. For these reasons, the use of these strategies can reduce people’s pain and suffer from natural disasters. In general, the application and effectiveness of sustainability dimensions and resilience strategies in the introduced humanitarian relief chain network were analyzed. Practical implications To verify the applicability of this study, this model is applied on a probable real-life case study in Tehran. Finally, some managerial insights are discussed to help humanitarian organizations, managers and stakeholders to make better decisions to reduce negative effects of natural disasters. Originality/value This paper introduced a two-stage stochastic mathematical model for designing a resilient humanitarian relief chain network under disruption, at pre- and post-disaster stages. Also, economic and social dimensions of sustainability are considered in this study. Moreover, assembling perishable and im-perishable relief items as relief kits, dynamically is a main contribution of this research.

Leveraging SDN for scalable and sustainable fat tree networks: a multi-objective performance and energy efficiency evaluation of an 8-pod fat tree data center

Modern data centers increasingly rely on Software-Defined Networking (SDN) to address challenges related to scalability, performance, and efficient resource management. This research investigates the scalability and performance optimization of fat-tree topology within SDN environments, focusing on the impact of a sleep mode technique on network efficiency and energy consumption. Using the Mininet emulator, an 8-pod fat-tree network is simulated and compared against traditional routing methods like Equal-Cost Multi-Path (ECMP) and Dijkstra’s algorithm. The findings show that the sleep mode technique improves bandwidth utilization and throughput by reducing energy consumption during low-traffic periods without significantly affecting data flow. In contrast, Dijkstra’s algorithm exhibited reduced throughput due to inefficient path management, while ECMP did not fully optimize load balancing or energy efficiency. The sleep mode approach efficiently redistributes traffic across active switches, preventing congestion and outperforming both Dijkstra and ECMP in terms of average load. The results demonstrate that implementing sleep mode in fat-tree SDN networks enhances both network performance and energy efficiency, offering a practical solution for large-scale data center operations. These findings provide valuable insights for optimizing SDN-based traffic management in modern network infrastructures.

Shipping Logistics Network Optimization with Stochastic Demands for Construction Waste Recycling: A Case Study in Shanghai, China

In this paper, we introduce a shipping logistics network optimization method for construction waste recycling. In our case, construction waste is transported by a relay mode integrating land transportation, shipping transportation, and land transportation. Under the influence of urban economic life, the quantity (demand) of construction waste is uncertain and stochastic. Considering the randomness of construction waste generation, a two-stage stochastic integer programming model for the design of a shipping logistics network for construction waste recycling is proposed, and an accurate algorithm based on Benders decomposition is presented. Based on an actual case in Shanghai, numerical experiments are carried out to evaluate the efficacy of the proposed model and algorithm. Based on an actual case study in Shanghai, numerical experiments demonstrate that the proposed model can help to reduce transportation costs of construction waste. Sensitivity analysis highlights that factors like the penalty for untransported waste and capacity constraints play a crucial role in network optimization decisions. The findings provide valuable theoretical support for developing more efficient and sustainable logistics networks for construction waste recycling.

Piping Material Selection in Water Distribution Network Using an Improved Decision Support System

This study introduces an integrated Multi-Criteria Decision Making (MCDM) methodology combining the Analytic Hierarchy Process (AHP), Entropy Weight Method (EWM), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to optimize the selection of municipal water supply pipeline materials. A comprehensive evaluation system encompassing thirteen criteria across technical, economic, and safety dimensions was developed to ensure balanced decision-making. The method employs a weight determination model based on Jaynes’ maximum entropy theory to harmonize subjective AHP-derived weights with objective EWM-derived weights, addressing inconsistencies in traditional evaluation approaches. This framework was validated in a case study involving a DN400 pipeline project in Jiaxing, Zhejiang Province, China, where five materials—steel, ductile iron, reinforced concrete, High-Density Polyethylene (HDPE), and Unplasticized Polyvinyl Chloride (UPVC)—were assessed using quantitative and qualitative criteria. Results identified HDPE as the most suitable material, followed by UPVC and reinforced concrete, with steel ranking lowest. Comparative analysis with alternative MCDM techniques demonstrated the robustness of the proposed method in balancing diverse factors, dynamically adjusting to project-specific priorities. The study highlights the flexibility of this approach, which can extend to other infrastructure applications, such as drainage systems or the adoption of innovative materials like glass fiber-reinforced plastic (GFRP) mortar pipes. By integrating subjective and objective perspectives, the methodology offers a robust tool for designing sustainable, efficient, and cost-effective municipal water supply networks.

Accelerating Benders Decomposition for sustainable food closed-loop supply chain network under uncertainty: a case study

PurposeThe purpose of this study was to address waste management in the food supply chain (FSC) through the integration of inspection processes in production and distribution centers under uncertain conditions, aiming to enhance sustainability across environmental, economic and social dimensions. The study introduces a sustainable forward and reverse FSC network using a closed-loop supply chain network approach to prevent the transfer of spoiled products, ultimately providing competitive advantages to stakeholders.Design/methodology/approachA robust multi-objective mathematical programming model is proposed, incorporating inspection processes to manage perishable products effectively. The model is solved using the Augmented Epsilon Constraint technique implemented in GAMS software, providing Pareto-optimal solutions tailored to decision-makers’ preferences. Furthermore, the methodology is applied in a real-world case study and solved with the Benders Decomposition algorithm to validate its practicality and effectiveness.FindingsThe proposed methodology effectively minimizes waste and enhances sustainability in the FSC by optimizing decision-making processes under uncertainty. The illustrative examples and real case study demonstrate the efficiency of the model and solution approach, highlighting the significant role of inspection in improving all three dimensions of sustainability.Practical implicationsThe study offers valuable insights into and tools for food industry managers to make informed strategic and tactical decisions. By addressing waste management through advanced supply chain modeling, the research helps organizations reduce costs, improve sustainability and gain a competitive edge in the market.Originality/valueThis research is novel in its focus on integrating inspection into the FSC network and addressing uncertainty through robust mathematical modeling. It contributes to the existing literature by demonstrating the impact of inspection on sustainability in FSCs and providing practical solutions for real-world implementation.

A Review of Transportation 5.0: Advancing Sustainable Mobility Through Intelligent Technology and Renewable Energy

Transportation 5.0 is an advanced and sophisticated system combining technologies with a focus on human-centered design and inclusivity. Its various components integrate intelligent infrastructure, autonomous vehicles, shared mobility services, green energy solutions, and data-driven systems to create an efficient and sustainable transportation network to tackle modern urban challenges. However, this evolution of transportation is also intended to improve accessibility by creating environmentally benign substitutes for traditional fuel-based mobility solutions, even when addressing traffic management and control issues. Consequently, to promote synergy for sustainability, the diversified nature of the Transportation 5.0 components ought to be efficiently and effectively managed. Thus, this study aims to reveal the involvement of Transportation 5.0 core component prediction in the sustainable transportation system through a systematic literature review. This study also contemplates the causal model under system dynamics modeling in order to address sustainable solutions and the movement toward sustainability in the context of Transportation 5.0. From this review, in addition to the developed causal model, it is identified that every core component management method in the sustainable Transportation 5.0 system reduces environmental impact while increasing passenger convenience and the overall efficiency and accessibility of the transport network, with greater improvements for developing nations. As the variety of transportation options, including electric vehicles, is successfully integrated, this evolution will eventually enable shared mobility, green infrastructure, and multimodal transit options.

The development and testing of a screening instrument for psychosocial needs assessment within acute psychiatric care

A new instrument (PSH-7) was developed and tested in practice for the standardised assessment of psychosocial support needs in acute psychiatric care.Based on a mixed-methods approach, this instrument was tested in a cross-sectional study (N=84) using quantitative (descriptive evaluation and univariate analysis of variance) and qualitative methods (qualitative content analysis) for its suitability for practical use.The PSH-7 proved to be a suitable instrument for recording the need for help. Loneliness, lack of daily structure and unemployment are the most frequently mentioned needs for help in the context of acute psychiatric care.The study supplements the international findings on the connection between psychosocial stress factors and the maintenance of mental illness. There should be an early focus on perspective planning and the organisation of a sustainable outpatient support network.

Role of Social Support Networks in Maintaining Mental Health & Well-being in Older Age: A Qualitative Review

Social support networks play a vital role in sustaining mental health & well-being and are gradually recognized as crucial especially in old age when people often experience unique challenges such as social isolation, decline of physical health & psychological stress. The purpose of this qualitative review is to explore the dynamics and effects of social support on older adults’ mental health by synthesizing findings from previous studies and inspecting the types of social support like emotional, instrumental, informational and companionship to mitigate the risks of depression, anxiety and cognitive decline. It also highlights the impact of various sources of social support such as the family, friends, community groups and the digital platforms. The factors like geographical distance, generational gaps and the stigma around help-seeking are also addressed which put hindrance. Findings of the study emphasize the importance sustainable support networks to increase resilience, reduce loneliness and promote overall health and well-being in older people. Some valuable recommendations for future research like exploring the role of technology-mediated supports and developing interventions tailored to specific demographic needs are also discussed.

Balancing economy, user guarantee, and carbon emissions towards sustainable natural gas pipeline network planning

Balancing economy, user guarantee, and carbon emissions towards sustainable natural gas pipeline network planning

A multi-objective robust optimization model to sustainable closed-loop lithium-ion battery supply chain network design under uncertainties

A multi-objective robust optimization model to sustainable closed-loop lithium-ion battery supply chain network design under uncertainties

Sustainable global semiconductor supply chain network design considering ESG

Sustainable global semiconductor supply chain network design considering ESG

A power-awareness routing protocol for sustainable low-power wireless networks: FPGA vs. microcontroller implementation

A power-awareness routing protocol for sustainable low-power wireless networks: FPGA vs. microcontroller implementation

Empirical effect of the Dr Lee Jong-wook Fellowship Program to empower sustainable change for the health workforce in Tanzania: a mixed-methods study.

This study evaluated the Dr Lee Jong-wook Fellowship Program's impact on Tanzania's health workforce, focusing on relevance, effectiveness, efficiency, impact, and sustainability in addressing healthcare gaps. A mixed-methods research design was employed. Data were collected from 97 out of 140 alumni through an online survey, 35 in-depth interviews, and one focus group discussion. The study was conducted from November to December 2023 and included alumni from 2009 to 2022. Measurement instruments included structured questionnaires for quantitative data and semi-structured guides for qualitative data. Quantitative analysis involved descriptive and inferential statistics (Spearman's rank correlation, non-parametric tests) using Python ver. 3.11.0 and Stata ver. 14.0. Thematic analysis was employed to analyze qualitative data using NVivo ver. 12.0. Findings indicated high relevance (mean=91.6, standard deviation [SD]=8.6), effectiveness (mean=86.1, SD=11.2), efficiency (mean=82.7, SD=10.2), and impact (mean=87.7, SD=9.9), with improved skills, confidence, and institutional service quality. However, sustainability had a lower score (mean=58.0, SD=11.1), reflecting challenges in follow-up support and resource allocation. Effectiveness strongly correlated with impact (ρ=0.746, P<0.001). The qualitative findings revealed that participants valued tailored training but highlighted barriers, such as language challenges and insufficient practical components. Alumni-led initiatives contributed to knowledge sharing, but limited resources constrained sustainability. The Fellowship Program enhanced Tanzania's health workforce capacity, but it requires localized curricula and strengthened alumni networks for sustainability. These findings provide actionable insights for improving similar programs globally, confirming the hypothesis that tailored training positively influences workforce and institutional outcomes.

Transparency and changing stakeholder roles in the digital age of sustainable agri-food supply chain networks

Society and policy demand greater sustainability of food systems, driving practitioners to improve the transparency of supply chain networks through digital innovation. Uncertainties regarding the structuring of relationships with primary and secondary stakeholders for sharing intangible data and information diminishes the potential for exploitation of digital transparency. While businesses are accustomed to organizing efficient flows of tangible goods, management research integrating digital transparency considerations to investigate and conceptualize structural changes in agri-food supply chain networks (AFSCNs) is scarce. This gap motivates the following four questions of this study: (1) Who are the primary and secondary stakeholders in the AFSCNs of the digital era? (2) What are their transparency interests? (3) How do AFSCN structures change with the emergence of digital innovations that can facilitate sustainability transition through greater transparency? (4) How to conceptualize those structural changes to AFSCNs? The netchain approach and respective transparency concept are integrated with classical stakeholder theory. Data was collected via a series of 21 semi-structured pilot interviews with technology providers in the EU agri-food sector and analyzed using structured content analysis. Results paint a complex picture of contemporary primary and secondary stakeholders of AFSCNs and their interests. Primary stakeholder interests lead to coopetition in vertical and horizontal relationships of the netchain and low transparency efforts by intermediaries. Both hamper the dissemination of digital innovations and the exploitation of their potential to improve AFSCN sustainability. Among secondary stakeholders, policymakers and governments, NGOs, and technology providers excel in being drivers of digital transparency for sustainability, with social media as a strong direct communication tool to reach netchain stakeholders, consumers, and research institutes/universities as collaborators and customers. The emergence of “information AFSCN” and “digital AFSCN” increases the complexity of the whole supply chain network through intermediation, reconfiguration, and emergence modes of change to underlying structures. Agri-food business managers, scientists, and policymakers should innovate in private and public governance to facilitate collaborative advantage and sustainability in a combination aligned with innovative digital transparency solutions.

The legitimation of private net zero emission building standards in the context of global decarbonization goals

Since the Paris Agreement – where nations committed to decarbonizing their economies – private net zero standards have proliferated. Yet, their limited scope and ability to deliver tangible change threatens their legitimacy. For some scholars, this reflects societies’ limited capacity to envision pathways towards a fossil-free future. This raises questions about how private net zero standards are legitimised. Combining insights from the literature on legitimation, discourse analysis, and sociotechnical transitions, we analyse the legitimation of Net Zero Carbon Buildings by the World Green Building Council, the strongest global sustainable construction network. We find that net zero standard legitimation is a dynamic multilevel, multistakeholder process based on three strategies: vertical nesting, ambivalence, and conflict avoidance. This process perpetuates assumptions about growth, authority, and appropriate scales of action. This incremental, emission-focused approach to decarbonization is shielded from critique through claims that it contributes to broader sustainability objectives. By reproducing institutionalized narratives, global standard setters create a sense of consensus. However, this perception of consensus fails to address the complexities of implementation, contextualization, and integration of broader environmental and social concerns. These findings raise doubts in both theory and practice about the capacity of the construction sector to decarbonize through current strategies.

Motif‐based resiliency assessment for cyber‐physical power systems under various hazards

AbstractCyber‐physical power systems (CPPS) are integral to meeting society's demand for secure, sustainable, affordable and resilient critical networks and services. Given the convergence of decarbonising, heating, cooling, and transportation networks onto cyber‐physical power systems (CPPS), this takes on increased significance. This paper introduces an innovative approach to the open challenge of how we evaluate CPPS resilience, presenting the use of network motifs and Monte Carlo simulations. We demonstrate how our methodology enables a comprehensive analysis of CPPS by capturing the interdependence between cyber and physical networks and by accounting for inherent uncertainties in cyber and physical components. Specifically, this method incorporates the dynamic interplay between the physical and cyber networks, presenting a time‐dependent motif‐based resilience metric. This metric evaluates CPPS performance in maintaining critical loads during and after diverse extreme events in cyber and/or physical layers. The resilience status of the system is determined using the prevalence of 4‐node motifs within the system's network, offering valuable redundant paths for critical load supply. The study models a variety of natural events, including earthquakes, windstorms, and tornadoes, along with cyber‐attacks while accounting for their inherent uncertainties using Monte Carlo simulation. The proposed approach is demonstrated through two test CPPS, specifically the IEEE 14‐bus and IEEE 30‐bus test systems, affirming its effectiveness in quantifying CPPS resilience. By comprehensively addressing system dynamics, interdependencies, and uncertainties, the proposed technique advances our understanding of CPPS and supports resilient system design.

How Bike-Sharing Affects the Accessibility Equity of Public Transit Systems—Evidence from Nanjing

This study examines how Free-Floating Bike-Sharing (FFBS) affects the accessibility equity of public transit sytems by serving as a first-mile feeder. To evaluate accessibility improvements for various opportunities within a 30-min travel time, we construct a complete travel chain approach based on multi-source, real-world data from Nanjing, China. The results indicate that FFBS significantly enhances accessibility, particularly for job opportunities and green spaces, with improvements of up to 180.02% and 155.82%, respectively. This integration also enhances the accessibility equity of public transit systems, particularly in green spaces, with a Gini coefficient improvement of 0.0336. Additionally, we find that areas with low housing prices exhibit greater accessibility inequality, while those with moderate housing prices benefit more from FFBS integration. These findings can potentially support transport planners in optimizing and managing FFBS and public transit systems to facilitate sustainable and inclusive transportation networks.

A resilient and sustainable supply chain network design: a case study in beverage industry

A resilient and sustainable supply chain network design: a case study in beverage industry

Various Hydrogel Types as a Potential In Vitro Angiogenesis Model.

Angiogenesis, the formation of new blood vessels, is a fundamental process in both physiological repair mechanisms and pathological conditions, including cancer and chronic inflammation. Hydrogels are commonly used as in vitro models to mimic the extracellular matrix (ECM) and support endothelial cell behavior during angiogenesis. Mesenchymal stem cells further augment cell and tissue growth and are therefore widely used in regenerative medicine. Here we examined the combination of distinct hydrogel types-fibrin, collagen, and human platelet lysate (HPL)-on the formation of capillaries in a co-culture system containing human umbilical vein endothelial cells (HUVECs) and bone marrow-derived mesenchymal stem cells (BM-MSCs). The mechanical properties and structural changes of the hydrogels were characterized through scanning electron microscopy (SEM) and nanoindentation over 10 days. Fibrin and HPL gels sustained complex network formations, with HPL gels promoting even vascular tube formation of up to 10-fold capillary caliber. Collagen gels supported negligible angiogenesis. Our results suggest that HPL gels in combination with MSC-EC co-culture may be employed to obtain robust vascularization in tissue engineering. This study provides a comparative analysis of fibrin, collagen, and HPL hydrogels, focusing on their ability to support angiogenesis under identical conditions. Our findings demonstrate the superior performance of HPL gels in promoting robust vascular structures, highlighting their potential as a versatile tool for in vitro angiogenesis modeling.

A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batteryless IoT Networks

The rapid advancement of Internet of Things (IoT) networks has revolutionized modern connectivity by integrating many low-power devices into various applications. As IoT networks expand, the demand for energy-efficient, batteryless devices becomes increasingly critical for sustainable future networks. These devices play a pivotal role in next-generation IoT applications by reducing the dependence on conventional batteries and enabling continuous operation through energy harvesting capabilities. However, several challenges hinder the widespread adoption of batteryless IoT devices, including the limited transmission range, constrained energy resources, and low spectral efficiency in IoT receivers. To address these limitations, reconfigurable intelligent surfaces (RISs) offer a promising solution by dynamically manipulating the wireless propagation environment to enhance signal strength and improve energy harvesting capabilities. In this paper, we propose a novel deep reinforcement learning (DRL) algorithm that optimizes the phase shifts of RISs to maximize the network’s achievable rate while satisfying IoT devices’ energy harvesting constraints. Our DRL framework leverages a novel six-dimensional chimp optimization algorithm (6DChOA) to fine-tune the hyper-parameters, ensuring efficient and adaptive learning. The proposed 6DChOA-DRL algorithm optimizes RIS phase shifts to enhance the received power of IoT devices while mitigating interference from direct and RIS-cascaded links. The simulation results demonstrate that our optimized RIS design significantly improves energy harvesting and achievable data rates under various system configurations. Compared to benchmark algorithms, our approach achieves higher gains in harvested power, an improvement in the data rate at a transmit power of 20 dBm, and a significantly lower root mean square error (RMSE) of 0.13 compared to 3.34 for standard RL and 6.91 for the DNN, indicating more precise optimization of RIS phase shifts.