Search Results (2,321)

The rapid expansion of online grocery shopping has intensified the need for strategically located distribution hubs that ensure efficient and sustainable operations. Traditional location models emphasize economic and logistical factors but often neglect energy efficiency and environmental sustainability. This paper proposes a hybrid decision-making model that integrates the analytic hierarchy process (AHP) and the spherical fuzzy technique for order of preference by similarity to ideal solution (SFTOPSIS) to address the complexities of delivery hub location selection. The AHP is used to determine the relative importance of key decision-making criteria, including cost, accessibility, infrastructure, competition, and sustainability, while SFTOPSIS ranks the candidate locations based on their proximity to the ideal solution. Spherical fuzzy sets allow for a more nuanced treatment of uncertainty, improving decision-making accuracy in dynamic environments. The results demonstrate that this hybrid approach effectively manages incomplete and uncertain data, delivering a robust ranking of candidate locations. By incorporating sustainability as a key factor, this study provides a structured and adaptive framework for businesses to optimize logistics operations in the post-pandemic landscape. The proposed methodology not only enhances decision-making in location selection but contributes to the development of more resilient and sustainable supply chain strategies. Full article

With the development of Internet of Things and artificial intelligence, large amounts of data exist in our daily life. In view of the limitations in current data security risk assessment research, this paper puts forward an intelligent data security risk assessment method based on an attention mechanism that spans the entire data lifecycle. The initial step involves formulating a security-risk evaluation index that spans all phases of the data lifecycle. By constructing a symmetric mapping of subjective and objective weights using the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM), both expert judgment and objective data are comprehensively considered to scientifically determine the weights of various risk indicators, thereby enhancing the rationality and objectivity of the assessment framework. Next, the fuzzy comprehensive evaluation method is used to label the risk level of the data, providing an essential basis for subsequent model training. Finally, leveraging the structurally symmetric attention mechanism, we design and train a neural network model for data security risk assessment, enabling automatic capture of complex features and nonlinear correlations within the data for more precise and accurate risk evaluations. The proposed risk assessment approach embodies symmetry in both the determination of indicator weights and the design of the neural network architecture. Experimental results indicate that our proposed method achieves high assessment accuracy and stability, effectively adapts to data security risk environments, and offers a feasible intelligent decision aid tool for data security management. Full article

Ecological carrying capacity (ECC) is central to assessing the sustainability of ecosystems, aiming to quantify the limits of natural systems to support human activities while maintaining biodiversity and resource regeneration. To assess ECC, earlier studies typically used the analytic hierarchy process (AHP) method for modeling. In this study, we developed an AHP-EW method based on a combination of AHP and the entropy weight method, which considered important indicators including land use, vegetation, soil, location, topography, climate, and socio-economics, and constructed an ECC evaluation system. The new AHP-EW method was applied to analyze the spatiotemporal ECC patterns in Urumqi from 2000 to 2020. The results showed a general decreasing trend in ECC during the period 2000–2020. Among them, the ECC decreased significantly by 19.05% from 2000 to 2010. After 2010, the rate of decline in ECC slowed to 14.12% due to ecological conservation policies. In addition, Midong District, Dabancheng District, and Urumqi County had worse ECC. Still, in general, the distribution of ECC in each district and county showed a trend of decreasing in areas with low ECC and increasing in areas with high ECC. Cluster analysis showed that ECC improved in ecological reserve areas, while some built-up areas showed a decrease in ECC due to economic development and human activities. Driving factor analysis shows that NDVI, climate change, and land-use conversion are the key factors influencing the change in ECC in Urumqi. This study provides new ideas and technical support for ECC assessment in arid areas, which can help formulate more effective ecological protection strategies and promote the healthy and stable development of regional ecosystems. Full article

Groundwater constitutes the primary source of liquid freshwater on Earth and is essential for ecosystems, agriculture, and human consumption. However, rising demand, urbanization, and climate change have intensified groundwater depletion, particularly in semi-arid regions. Therefore, assessing groundwater recharge zones is essential for sustainable water resource management in vulnerable areas such as Dera Ismail Khan, Pakistan. This study aims to delineate groundwater potential zones (GWPZs), using an integrated approach combining the Geographic Information System (GIS), remote sensing (RS), and the analytical hierarchy process (AHP). Twelve factors were identified in a study conducted using GIS-based AHP to determine the groundwater recharge zones in the region. These include land use/land cover (LULC), rainfall, drainage density, soil type, slope, road density, water table depth, and remote sensing indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Moisture Stress Index (MSI), Worldview Water Index (WVWI), and Land Surface Temperature (LST). The results show that 17.52% and 2.03% of the area have “good” and “very good” potential for groundwater recharge, respectively, while 48.63% of the area has “moderate” potential. Furthermore, gentle slopes (0–2.471°), high drainage density, shallow water depths (20–94 m), and densely vegetated areas (with a high NDVI) are considered important influencing factors for groundwater recharge. Conversely, areas with steep slopes, high temperatures, and dense built-up areas showed “poor” potential for recharge. This approach demonstrates the effectiveness of integrating advanced remote sensing indices with the AHP model in a semi-arid context, validated through high-accuracy field data (Kappa = 0.93). This methodology offers a cost-effective decision support tool for sustainable groundwater planning in similar environments. Full article

The rapid urbanization in the Kabul River Basin has increased the demand for water for both drinking and commercial purposes, leading to domestic and industrial water insecurity. Assessing the groundwater potential of the Kabul River Basin is highly crucial for effective water management. The aim of this paper is to identify potential zones for groundwater by employing a Geographic Information System and an Analytical Hierarchy Process approach to formulate a cumulative score based on seven thematic images—rainfall, geology, lineament density, drainage density, land use/land cover, soil type, and slope—within the Kabul River, with assigned weightages of 32%, 27%, 12%, 10%, 8%, 6%, and 5%, respectively, with a consistency ratio of 0.053 (5%), demonstrating the reliability of the results. The study shows that the first three factors contribute more to the percentages of Groundwater Potential Zones. The identified groundwater potential is classified into very good, good, medium, poor, and very poor zones, covering 35.45% (19,989 km²), 37.2% (20,978 km²), 23.16% (13,063 km²), 4.13% (2332 km²), and 0.06% (19 km²), respectively. Groundwater potential in the basin is predominantly classified as good to medium; however, there are notable variations across sub-basins. The Swat sub-basin and western parts of the Kabul River Basin, encompassing the Panjshir and Parwan districts, exhibit exceptionally high groundwater potential. In contrast, the Panjkora sub-basin (Dir district) and southwestern areas of the Kabul River Basin, covering parts of the Ghazni and Wardak districts, have very limited groundwater potential. Full article

The Great Wall of China, one of the nation’s most remarkable military defense structures, possesses a history spanning several millennia and is associated with numerous heritage sites. Today, it stands as a world-renowned cultural heritage asset. Vegetation growing on the ruins of the Great Wall can exert both detrimental and protective effects on the structure. Indiscriminate removal of such vegetation may lead to unintended damage to the heritage site. Drawing on the theory of “evaluative conservation”, this study integrates the analytic hierarchy process (AHP) and the Delphi method to develop a resistance assessment system for vegetation removal. A case study was conducted on 40 plant species or categories located along the Ming-era Guangwu section of the Great Wall, with spatial zoning analysis applied to inform removal strategies. The results reveal the structure, key factors, and classification criteria of the resistance evaluation system. Corresponding management recommendations are proposed, including strategies such as “preservation”, “partial preservation”, “removal”, and “subsequent removal and management”. This research provides a foundational reference for the conservation and restoration of the Great Wall heritage, and for the management of associated vegetation. Full article

Rapid urbanization in Karachi, Pakistan, has resulted in increased impervious surfaces, leading to significant challenges, such as frequent flooding, urban heat islands, and loss of vegetation. These issues pose challenges to urban resilience, livability, and sustainability, which further demand solutions that incorporate urban greening and effective water management. This research uses remote sensing technologies and Geographic Information Systems (GISs), to analyze current surface treatments and their relationship to Karachi’s blue-green infrastructure. By following this approach, we evaluate flood risk and identify key flood-conditioning factors, including elevation, slope, rainfall distribution, drainage density, and land use/land cover changes. By utilizing the Analytical Hierarchy Process (AHP), we develop a flood risk assessment framework and a comprehensive flood risk map. Additionally, this research proposes an innovative Sponge City (SC) framework that integrates nature-based solutions (NBS) into urban planning, especially advocating for the establishment of green infrastructure, such as green roofs, rain gardens, and vegetated parks, to enhance water retention and drainage capacity. The findings highlight the urgent need for targeted policies and stakeholder engagement strategies to implement sustainable urban greening practices that address flooding and enhance the livability of Karachi. This work not only advances the theoretical understanding of Sponge Cities but also provides practical insights for policymakers, urban planners, and local communities facing similar sustainability challenges. Full article

Manufacturing organisations face increasing pressure to assess and report their sustainability performance, particularly with the introduction of the European Sustainability Reporting Standards (ESRS). This paper presents a novel sustainability assessment framework that integrates ESRS guidelines with the Analytic Hierarchy Process (AHP) to provide a comprehensive evaluation methodology for manufacturing organisations. The framework addresses the limitations of existing approaches by systematically incorporating standardised sustainability indicators while enabling precise weighting of their relative importance. Through a structured approach, the framework evaluates environmental, social, and governance dimensions using both measurable and non-measurable indicators derived from ESRS guidelines. The methodology includes automated pairwise comparisons and weight calculations, significantly reducing the complexity traditionally associated with multi-criteria decision-making methods. The framework’s effectiveness is demonstrated through its implementation in a manufacturing organisation, where it successfully evaluated 38 sustainability indicators across 10 ESRS-defined subtopics. The case study highlighted areas requiring immediate attention, particularly in water and marine resources management, where performance fell below the established benchmark. This research contributes to both theory and practice by offering manufacturing organisations a structured approach to sustainability assessment that combines regulatory compliance with effective performance evaluation. The framework’s automated nature and integration of standardised reporting requirements make it particularly valuable for organisations transitioning to mandatory sustainability reporting under ESRS guidelines. Full article

Choosing the optimal path in planning is a complex task due to the numerous options and constraints; this is known as the trip design problem (TTDP). This study aims to achieve path optimization through the weighted sum method and multi-criteria decision analysis. Firstly, this paper proposes a weighted sum optimization method using a comprehensive evaluation model to address TTDP, a complex multi-objective optimization problem. The goal of the research is to balance experience, cost, and efficiency by using the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) to assign subjective and objective weights to indicators such as ratings, duration, and costs. These weights are optimized using the Lagrange multiplier method and integrated into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. Additionally, a weighted sum optimization method within the Traveling Salesman Problem (TSP) framework is used to maximize ratings while minimizing costs and distances. Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. The study then introduces the Lagrange multiplier method to the algorithms, improving the solution quality of all seven heuristic algorithms, with an average solution quality improvement of 112.5% (from 0.16 to 0.34). The PSO algorithm achieves the best solution quality. Based on this, the study introduces a new variant of PSO, namely PSO with Laplace disturbance (PSO-LD), which incorporates a dynamic adaptive Laplace perturbation term to enhance global search capabilities, improving stability and convergence speed. The experimental results show that PSO-LD outperforms the baseline PSO and other algorithms, achieving higher solution quality and faster convergence speed. The Wilcoxon signed-rank test confirms significant statistical differences among the algorithms. This study provides an effective method for experience-oriented path optimization and offers insights into algorithm selection for complex TTDP problems. Full article

The ecological restoration of oyster reef ecosystems enhances their ecological functions and strengthens carbon sequestration capacity in coastal zones. Identifying suitable restoration sites is a crucial prerequisite for initiating oyster reef restoration projects. This study developed an oyster reef restoration suitability index model for the Tianjin coast of Bohai Bay by integrating the Analytic Hierarchy Process (AHP) with the Geographic Information System (GIS). It was then applied to assess the region’s suitability for oyster reef restoration. The suitability analysis identified favorable environmental conditions for oyster reef restoration in most of the Tianjin coastal area, with high suitability for factors like dissolved oxygen, pH, and seabed slope. However, excessive water depth in the eastern bay mouth and strong currents in the southwestern region made these areas unsuitable. The northern and western coastal regions were deemed optimal restoration sites, while proximity to shipping lanes and industrial activities limited feasibility in some nearshore zones. The model outputs exhibited strong spatial concordance with existing oyster reef distributions, validating its predictive accuracy. This framework offers a robust foundation for oyster reef restoration planning, with an adaptable index system that allows for regional extrapolation. By leveraging this model, decision-makers can systematically evaluate site-specific restoration suitability, optimize resource allocation, and guide strategic conservation planning. Full article

Accessible housing plays a vital role in promoting independent living and quality of life for people with disabilities. However, the existing design standards often fail to address the specific needs of diverse disability groups. This study aims to establish architectural and habitability criteria for housing adapted to various disabilities, including wheelchair users, individuals with achondroplasia (little people), Autism Spectrum Disorder (ASD) and Down syndrome, individuals with visual and hearing impairments, and older adults, by integrating international frameworks and prior research. The Analytic Hierarchy Process (AHP) was used to prioritize key factors in the housing design. The factors analyzed included autonomy, independence, safety, comfort, communication, and mobility. Findings reveal that autonomy consistently emerged as the most relevant criterion across groups, particularly for older adults (61.8%), wheelchair users (83%) and little people (64%). Secondary priorities varied: mobility was emphasized by wheelchair users (77%), communication by visually impaired individuals (64%), and comfort by deaf and hard of hearing participants (43%). The results underscore the need for housing solutions that reflect the priorities of each disability group. This study contributes by validating user-centered design criteria and offering a framework to guide inclusive housing policies and practices. By highlighting needs, it bridges the gap between generic accessibility standards and design. These findings support policy development and enrich the literature by incorporating unique resident-centered perspectives and overlooked indicators of housing accessibility and inclusive residential design. Full article

Popayán (Colombia) was the first city to be designated a UNESCO Creative City of Gastronomy in 2005, positioning itself as a symbolic ‘myth of origin’ within the network. In the context of growing demands for local strategies aligned with the Sustainable Development Goals (SDGs), it is pertinent to understand how founding cities manage and project their image through sustainable tourism marketing. Almost two decades later, this study examines how Popayán communicates and sustains its image within the UNESCO Creative Cities Network (UCCN), guided by sustainable tourism marketing principles. Methodologically, the study adopts an exploratory and descriptive case study approach, based on documentary analysis of institutional sources and the application of the adapted Analytic Hierarchy Process Image—UNESCO Creative City Gastronomy (AHPI-UCCG) model. The results provided the following: (1) a multidimensional analysis of Popayán’s image in the context of sustainable marketing; (2) an assessment of how the city’s image responds to current branding challenges, using the adapted AHPI-UCCG model; and (3) a proposal for a context-sensitive investment agenda aligned with sustainability objectives. These results support the development of a personalised strategy for Popayán and demonstrate the potential of this approach to inform analyses of other Creative Cities of Gastronomy, while recognising the unique symbolic role of Popayán as the foundational case. Full article

Transportation infrastructure serves a pivotal role in driving regional development. This study proposes a decision-making framework for rural road network planning within the context of China’s common prosperity initiative. An integrated model combining Data Envelopment Analysis (DEA) and the Analytic Hierarchy Process (AHP) is developed, where DEA is employed to identify technically efficient planning alternatives and AHP is used to rank these alternatives based on social and environmental benefits. Applying the model to the case of Yueqing City, Zhejiang Province, the findings reveal that common prosperity-oriented schemes, particularly the Scheme, which emphasizes full industrial coverage and balanced equity, achieve a superior balance among construction costs, industrial coverage, regional equity, and carbon emissions. Theoretically, this research advances transportation planning by incorporating equity-focused metrics, such as the Gini coefficient, into efficiency analyses, thus promoting a socially sustainable approach to infrastructure development. Practically, the proposed method offers a systematic and actionable tool for local governments to optimize rural transportation networks in support of common prosperity and balanced regional growth. The resulting framework not only identifies technically efficient and equitable layouts but also offers planners a transparent tool for balancing cost, social equity, and environmental impact in future rural infrastructure projects. Full article

The understanding of sustainability is shifting from that of a purely environmental dimension to one that includes social concerns. Combined with the growing customer interest in livestock husbandry practices, this study investigates the assessment of animal welfare as a socially influenced impact category for the life cycle assessment (LCA) of pig farming. The weighting of animal welfare impacts is based on a quantitative approach using a set of indicators derived from an expert survey using the Analytic Hierarchy Process (AHP). The aim is to develop an easy-to-implement score that translates the characteristics of several animal welfare indicators into a comparable value. To demonstrate the feasibility of the weighting part of the framework, a case study is conducted with nine experts in the fields of animal husbandry, agricultural sciences, and veterinary medicine. The case study results show that the main criteria of single animal observation and feed intake are the most relevant factors, at 30.6%, followed by operation-specific parameters at 23.9% and husbandry conditions at 14.9%. This case study highlights that animal losses (13.9%) significantly influence the impact category, while access to outdoor areas (1.4%) is less important. The overall conclusion is that an animal health-centered approach is preferable when assessing animal welfare. Full article

Dealing with the challenge of urban sustainability, especially after the COVID-19 pandemic, requires a holistic approach to urban mobility planning. While numerous mobility assessment frameworks exist for developed regions, there remains a significant gap in methodologies adapted to Global South contexts because they do not incorporate governance dimensions and citizen perspectives. This research addresses this gap by developing and validating a comprehensive assessment framework that extends beyond the traditional sustainability triad to include governance aspects. Our research question explores how a hybrid evaluation approach combining objective measurements with subjective citizen perceptions can enhance mobility assessments in resource-constrained environments. The proposed model comprises four dimensions (environmental, social, economic, and governance), eight sub-dimensions, and thirty-six indicators, with weights assigned through the Analytic Hierarchy Process (AHP) by diverse mobility experts. The methodology was validated in two intermediate Colombian cities, demonstrating its applicability in contexts with limited availability of data. The results highlight gaps in mobility policies due to discrepancies between official measurements and citizen perceptions. This assessment framework offers a practical instrument for urban mobility decision-makers in Global South cities, enabling evidence-based prioritization while ensuring that citizen needs remain central to sustainable transportation planning. Full article