Search Results (38)

University campuses face significant challenges in balancing energy efficiency, renewable energy adoption, and sustainable transportation while meeting budgetary constraints and sustainability goals. While existing optimization approaches typically address these as separate problems, this study presents an innovative multi-objective optimization framework that integrates building efficiency, renewable energy, electric vehicle charging, and sustainability scoring criteria into a unified model. The approach formulates a mixed-integer non-linear programming model with three competing objectives: minimizing primary energy consumption, minimizing investment cost, and maximizing sustainability metrics, addressing the critical need for comprehensive campus energy management tools. The optimization model was applied to the R&D Park Building of Erciyes University, utilizing actual building parameters, time-variable electricity pricing, and commercially available renewable energy technologies. Our analysis of the Pareto-optimal solutions reveals distinct trade-offs between the objectives, with primary energy consumption ranging from 1,317,860 to 4,642,770 GJ/year, investment costs between $25,735 and $485,674, and sustainability scores between 366 and 1034. Most significant for practical implementation is the balanced performance solution ($127,064), which achieves minimum energy consumption (1,367,010 GJ/year) while securing a substantial sustainability score of 538 points. The results demonstrate that while inherent trade-offs exist between competing objectives, significant sustainability improvements are achievable at intermediate investment levels, making meaningful environmental progress accessible to a broad spectrum of higher education institutions. This comprehensive optimization framework provides campus administrators with a practical decision-support tool for aligning energy systems with institutional priorities, budgetary constraints, and sustainability commitments. Full article

Electrification is a key priority of the European Union, focusing on saving energy resources and mitigating carbon emissions through enhancing restrictions on relative policies and initiatives. For such goals to be achieved, investing in renewable energy technologies on large- and small-scale projects is promoted. These efforts were implemented in the building sector too, highlighting the importance of optimal decisions in improving the energy performance of buildings, from an economic, energy and environmental perspective. In this context, this paper aims to elaborate a decision-making methodology for building thermal design, considering the optimal selection and operation of multi-energy systems focused on renewable technologies. Solar thermal collectors, photovoltaic systems and heat pumps were included in an Energy Hub for meeting the heating, cooling and domestic hot water energy demand. Optimal decisions were achieved by formulating Mathematical Programming models in GAMS, for minimizing economic, energy and environmental parameters of the systems under a life cycle perspective. The proposed methodology was implemented in a residential building case study. Results show that combining heat pumps with photovoltaics is preferable for all of the examined criteria, while a sensitivity analysis of the economic, energy and environmental parameters, influencing the energy mixture, leads to optimal solutions with the participation of different energy systems. Full article

Currently, the need for a clean transition has made the upscaling of sustainable energy investment projects imperative. This paper addresses the increasing importance of sustainable energy investment projects in the context of climate change and the urgent need for a global energy transition. Given the complexity of decision-making in this field, a multi-criteria decision-making (MCDM) approach is employed to assess the main criteria considered by project developers and financial institutions. Using the Analytic Hierarchy Process (AHP) method, eight criteria are identified and evaluated. Results highlight differing priorities between project developers and investors, emphasizing the need for adaptable approaches to accelerate sustainable energy investments. The study underscores the importance of understanding diverse stakeholder preferences and priorities in formulating effective strategies and managing associated risks to effectively promote sustainable energy projects. Future research should focus on real-life case studies and policy assessments to further enhance the understanding of sustainable energy investment dynamics. Full article

The accurate prediction of China’s energy consumption and CO₂ emissions is important for the formulation of energy and environmental policies and achieving carbon neutrality. This paper proposes a new weighted error evaluation criterion that emphasizes the importance of new data, thereby enabling more accurate capture of the variation characteristics of new data and reflecting the principle of new information priority. By optimizing the development coefficient, grey action, and parameters in the time response formula of the traditional GM(1,1), a novel optimized model, OGMW(1,1), is constructed. The accuracy of the new model is verified by three cases from the literature. The future trends of primary energy, oil, and coal consumption and CO₂ emissions in China are predicted over the next five years. The conclusions are as follows: First, the new weighted error evaluation criteria are effective and reasonable and can indicate whether a grey model can reliably use the most recent information for modeling. Second, based on the new error evaluation criteria, the development coefficient, ash action, and parameter C in the time response function can be optimized. The results show that the optimization method is reasonable. Third, compared with the traditional models GM, GMO, and ARIMA, the OGMW(1,1) provides better simulation and prediction accuracy, and new information can be prioritized more effectively. Fourth, the forecasting results indicate that China will increase its consumption of primary energy, oil, and coal, as well as its CO₂ emissions. Notably, the growth rates of primary energy and oil consumption are high at approximately 22.7% and 25%, coal consumption will increase slightly, and CO₂ emissions will increase by approximately 11%. Full article

The construction industry plays a crucial role in contributing to the economy and developing sustainable infrastructures. However, it is known as one of the most dangerous industrial domains. Over the years, special attention has been paid to developing models for managing and planning construction safety. Many research studies have been carried out to analyze the root causes of fatal accidents in construction sites to develop models for preventing them and mitigating their consequences. Root cause identification and analysis are essential for effective risk mitigation. However, implementing mitigation activities is usually limited to the project’s safety budget. The construction sector suffers from a lack of allocation of appropriate safety resources triggered by a dynamic and complex project environment. This study aims to address the gap in safety resource allocation through a comprehensive root cause analysis of construction work accidents. In this paper, we present a comprehensive review of work accident-related research, categorized according to the 5M model into five root factors: medium, mission, man, management, and machinery. A novel methodology for construction safety resource allocation is proposed to mitigate risks analyzed by the 5M model with the aid of advanced technological solutions. Safety resource allocation alternatives are formulated, and their priorities are established based on an analysis of structured criteria that integrate both risk and cost considerations. The Analytical Hierarchy Process (AHP) is employed to select the optimal alternative for safety resource allocation, with the objective of effective risk mitigation. The proposed model underwent validation through two different case studies. The findings indicate that risk aversion is a critical factor in the optimal allocation of safety resources. Furthermore, the results suggest that regulatory measures should prioritize the stimulation of risk motivation in the safety decision-making processes of construction firms. Full article

The high rate of depredation of forest resources causes major climatic changes that affect the economic activities and health of populations, plunging them into poverty and social problems. The state is responsible for dealing with these problems, because it has the technical, legal, and economic power to do so. This research aims to identify the factors that limit the design and formulation of public policies for the conservation of natural resources at the level of local district and provincial governments in Peru. For this study, we used qualitative methodology and non-probabilistic sampling, as well as techniques such as unstructured interviews, focus groups, and documentary review; moreover, for data analysis, we applied the theoretical saturation design in grounded theory. The results show that the conservation of natural resources is not positioned as a priority public policy in municipal administrations; furthermore, the organic units of natural resources suffer financial restrictions, and not because of a lack of budget availability, but because of a lack of will and decision-making capacity of authorities and civil servants, as well as a lack of coordination between the different national governments. It concludes that there are conflicts of interest in public policy making, with abuse of power and corruption predominating. Furthermore, the complexity of addressing sustainability criteria and the inability to confront the environmental crisis mean that international summits and national norms are attenuated in the face of the problems of environmental degradation. Deforestation should be considered a major public priority problem because of its environmental, economic, social, and health impacts. These problems require a holistic approach that combines local, national, and international policies and fosters effective and participatory governance. Full article

The paper is dedicated to the multi-criteria choice of an optimal variant of a pressure relief valve with a nominal pressure of 3 bar, manufactured from four different materials. The paper includes the usage of a number of existing methods that are combined in an appropriate way to solve a specific practical problem, and a sequence of steps for their effective application is formulated. The optimization is defined and analyzed, and a seven-stage solution approach is developed. A list of requirements for the product is composed. The requirements are organized into objective groups, and an objective tree is developed. Metrics for measuring the requirements are defined. The “House of Quality” tool is used for correlating the metrics and requirements. Based on these correlations, criteria are selected for the evaluation of alternative variants. A mathematical model of the problem is built, and the evaluation criteria are defined in terms of concrete values for the variants, transforming the criteria into objective functions. A normalization method for the objective functions is selected and a principle of optimality is chosen. Using a known method for defining objective functions’ priorities, the weighting factors for different priority scenarios are obtained. The results of the optimization are shown for the different scenarios in relation to the different priorities (importances) of the selected criteria. Seven optimization problems are solved, and three different solutions are found. The solutions are graphically represented on a radar chart. All solutions found are optimal according to the selected criterion for optimality and calculated weight vectors. The final solution, chosen among the optimal ones found, is selected on the basis of additional decision makers’ considerations. Full article

The color of urban streets plays a crucial role in shaping a city’s image, enhancing street appeal, and optimizing the experience of citizens. Nevertheless, the relationship between street color environment and residents’ perceptions has rarely been deeply discussed, and most of the existing studies adopt qualitative methods. To accurately and effectively assess the connection between street color environment and residents’ emotional perceptions, this paper introduces a quantitative research framework based on multi-source data called “Color Emotion Perception with K-Means, Adversarial Strategy, SegNet, and SVM (CEP-KASS)”. By combining K-Means unsupervised machine learning and SegNet computer vision techniques, it captures and analyzes visual elements and color data from Baidu Street View Images (BSVI). It then employs a human–machine adversarial scoring model to quantify residents’ perceptions of BSVI and uses the support vector machine regression model to predict the final perception scores. Based on these data, a Pearson correlation analysis and visual analysis were conducted on the elements and color in the urban environment. Subsequently, the streets were classified based on perception frequency and perception scores by integrating multi-source data, and areas within the third ring of Xuzhou City were selected for validating the research framework. The results demonstrate that utilizing street-view images and the CEP-KASS framework can quantitatively analyze urban color perception and establish a connection with residents’ emotions. In terms of color perception, red, orange, and blue all have a strong positive correlation with the interesting score, whereas black is positively correlated with a sense of safety. Regarding color attributes, low-saturation bright colors result in higher fun perception scores in urban spaces; too low saturation and brightness can affect their attractiveness to residents; brightness has an inverse relationship with the perception of safety, and adjusting brightness inversely can improve the perceived safety experience in certain urban external spaces. The street classification criteria based on perception frequency and perception scores proposed herein can provide references for planners to prioritize color transformation decisions, with a priority on emulating HSHF streets and transforming LSHF streets. When formulating color planning, suggestions for color adjustment can be given based on the correlation study of color with visual elements and perception scores, optimizing urban residents’ spatial perception and their emotional experiences. These findings provide robust theoretical support for further enhancing the visual quality of streets and refining urban color planning. Full article

Coal chemical industry (CCI) sites are characterized by complex environmental media, combined heavy metal pollution, and diverse exposure routes. However, existing human health risk assessment (HHRA) methods have multiple drawbacks, such as their small scope of application, limited assessment factors, and insufficient case applications. After 128 soil samples were collected, the contents of Be, V, Ni, Cu, Zn, As, Cd and Hg in the soils were analyzed based on general risk assessment guideline of China. Then, risk levels were calculated based on oral ingestion, skin contact and inhalation as the main exposure routes to compare and screen priority heavy metals. Furthermore, control values were identified through a contribution rate calculation model when CR > 10⁻⁶ or HQ > 1. As reference values, risk thresholds were proposed for heavy metals, and then a soil HHRA framework for the CCI site was constructed. Under the three exposure routes, the total CR was As > 10⁻⁶, and the total HQ was 1 > As > Cd; the HHRs related to As and V via the oral ingestion, dermal contact, and inhalation pathways were 76.67%, 13.13%, and 10.18% and 1.66%, 0, and 98.34%, respectively. The risk control value of As was 1.59 mg/kg and that of V was 25.1 mg/kg. Based on these results, the threshold values for priority heavy metals should be based on comprehensive considerations of the elemental background of a specific area, the contaminant criteria in different areas, the regional industrial development plan, and the most important control criterion, as well as the control value. Through the development of an HHRA framework and case verification, the authors of this article aim to guide CCI managers in screening priority heavy metals, formulating protection measures, developing improved operational procedures and improving the HHRA system for polluted CCI sites. Full article

In the present article, the solution for choosing the optimal structural variant of an industrial robot for extracting castings from die casting machines is considered. For this purpose, the process of extracting the castings from the mold is analyzed. On this basis, functions are defined, and a functional structure of the robot is built. Alternative variants of devices for each function are developed. The set of possible structural variants are constructed, considering the compatibility between devices and the possibility of performing more than one function with one device. The problem of choosing an optimal structural variant is formulated, and its characteristic features are determined. The main stages of a methodology and application software for the problem’s solution are presented. After an analysis of requirements for the extractor, the set of criteria for evaluating the structural variants are determined. The set includes criteria that minimize the production costs, production floor space, as well as the energy costs in the operation process, which is of particular importance in the conditions of global energy crisis. A mathematical model of the problem is built. The formulated multi-criteria optimization problem is solved, both with equal objective functions and with different priority. Full article

Mass casualty incident (MCI) is an unpredictable situation where a great number of people have been injured after an accident or sudden disease. Survival of the injured in the MCI depends on the efficiency of the directed emergency system (DES). The organization and management of medical assistance is of paramount importance. The shortest possible time to provide medical services to injured persons is crucial. The medical service in the case of the MCI primarily requires decisions on the priority of the order of treatment of the injured, the choice of medical transport and the location of specialized emergency treatment. As part of this paper, the effectiveness of the DES has been analyzed, and criteria used to improve rescue operations have been formulated. A formalized mathematical description of the medical rescue operations in MCIs has been proposed, and the optimization problem as the mixed integer linear programming (MILP) task was formulated. Optimization of an example case of rescue operations in MCIs has been presented. A computer simulator for optimal decision-making in medical rescue operations (CSMRO) has been developed for this purpose. The CSMRO implements various multi-criteria optimization methods to solve the formulated problem of rescue operations optimization. The results of computations made with the developed CSMRO simulator significantly shorten the time of decision-making in mass casualty incident handling. Full article

Simplicity and optimality are commonly associated with the particle swarm optimization (PSO) algorithm. As a result, numerous variants and hybrids of PSO have been developed and implemented to address structural optimization problems. The undeniable importance of the initialization technique in determining the overall performance of a given optimization algorithm cannot be overstated. Optimization algorithms, such as PSO, typically rely on a random, uniformly distributed initialization. Through multiple iterations and updates, these algorithms aim to achieve optimal results. The underlying assumption behind such an initialization approach is that a fair or reasonable arrangement of particles is best accomplished through randomization, and thus the entire optimization process is iterated based on this assumption. However, this initialization technique raises concerns regarding the attainment of optimality and convergence, leaving room for further examination. In this paper, we challenge this assumption by introducing a priority concept. The key idea is that particles should not be initialized randomly since randomness alone does not guarantee a reasonable allocation of design variable values in iterative optimization. This can lead to misguided velocity updates and ultimately, a time-consuming pursuit of optimality. To address this issue, we formulate priority criteria (PC) and propose an enhanced PSO variant called Priority Criteria PSO (PCPSO). The PC can be incorporated into any PSO variant or hybrid without impacting the parameter settings, constraints, and penalty approaches of the respective algorithms. A case study involving 2D reinforced concrete frames was conducted to compare the performance of the ordinary PSO algorithm with the PCPSO. The results clearly demonstrate that the introduction of the PC leads to a significant cost reduction when compared to PSO with an inertia damping factor. Additionally, the PCPSO algorithm exhibits accelerated convergence. Furthermore, to alleviate the computational burden associated with structural analysis at each iteration, a reanalysis approach called Combined Approximations (CA) is mathematically formulated and implemented. Full article

This paper deals with problems of freight transport sustainability from the perspective of four key factors: greenhouse gas production, fossil fuel dependence, congestion, and accident rates. It is based on the results of the FreightVision project, in which the author participated as a researcher and member of the design team. The aim was to develop a set of 35 recommendations to serve as a tool for European Union decision-making in transport policy matters at the highest level. The developed measures were prioritized, and a list of individual recommendations was drawn up according to their potentials. Then, the set of measures was processed using multi-criteria analysis tools, and these results were compared with the original list using comparative analysis to identify differences between the two approaches. The contribution of this work is the development of a methodology for evaluating the traffic measures according to their priorities and, at the same time, the verification of the empirical results thus obtained with the results that were the output of the mathematical processing. This work fills a research gap in a similar problem area by working with specific measures systematically developed for the purposes of analysis; these results are used to formulate recommendations for the European Commission whose policy decisions should lead to an increased level of freight transport sustainability. Full article

Land use conflicts exacerbate soil erosion and reduce biodiversity, which is detrimental to sustainable development. Multiple methods such as multi-criteria evaluation and landscape pattern indexes can identify land use conflicts, but few studies conform to the concept of green development. The concept of green development gives priority to ecological protection and coordinates the relationship between production development, food production and ecological protection to achieve sustainable development. Taking Jinan City (China) as the study area, we identified the ecological source areas by evaluating the importance of ecosystem service functions and ecological sensitivity, then extracted and optimized the ecological corridor network (using the minimum cumulative resistance model and gravity model), and constructed the ecological security pattern. Spatial overlay analysis of cultivated land, construction land, and the ecological security pattern was performed to identify the types and intensity of land use conflicts. Spatially, we found that ecological land was in more serious conflict with cultivated land than construction land. Different types of land use conflicts have significant differences in spatial distribution. The key to land use conflict mediation in Jinan City is to balance food security with the improvements in the quality of the ecological environment. Hence, it is necessary to delineate the main functional zones and formulate tailored land use conflict mediation strategies in each zone. The method for land use conflict identification proposed here follows the principle of giving priority to ecological protection, providing a scientific reference for the utilization and protection of territorial space in other similar areas. Full article

China and Russia have different interests in the Arctic but are forced to look for possible ways of cooperation in energy projects in the current external conditions. This changes the priorities of both countries and, accordingly, transforms the risks. Objectives of the research: to build an algorithm for identifying anthropogenic environmental risks in the context of two major players economic activities in the Arctic region: the Russian Federation and China. In the paper, we formulated an algorithm of environmental risk identification. We identified environmental hazards from the main parameter—the type of economic activity for the extraction of energy resources, premises, and factors for the occurrence of environmental hazards and compiled criteria for risk selection. Methods used: complex analysis (mixed method research): empirical and comparative methods, methods of expert assessments, the method of inductive statistics (inferential statistics) to compare the perception of risk at the level of different groups. Results: the algorithm has been formed for determining risks in the changed external conditions. Major anthropogenic environmental risks are identified from the perspective of the main players in the Arctic—Russia and China, which can help to make the necessary decisions on time and partially prevent environmental degradation. This makes it possible to identify the risks associated with conducting economic activities for the extraction of energy resources in the Arctic region. Therefore, this study contributes to a more accurate identification of anthropogenic environmental risks in the Arctic region. Full article