A new rough ordinal priority-based decision support system for purchasing electric vehicles.

This study proposes a novel multi-criteria decision-making (MCDM) model based on a rough extension of the Ordinal Priority Approach (OPA) to determine the order of importance of users' perspectives on Electric Vehicle (EV) purchases. Unlike conventional methods that rely on predefined ranks for criteria weighting coefficients, the proposed rough OPA method employs an aggregated rough linguistic matrix, enabling a more precise and unbiased calculation of interval values. Moreover, the model addresses inherent uncertainties by incorporating nonlinear aggregation functions, accommodating decision makers' risk attitudes for flexible decision-making. To validate the model's efficacy, a large-scale post-EV test drive survey is conducted, enabling the determination of relative criterion importance. Sensitivity analysis confirms the robustness of the model, demonstrating that marginal changes in parameters do not alter the ranking order. The results unveil the significance of the reliability criterion and reveal that vehicle-related characteristics outweigh economic and environmental attributes in the decision-making process. Overall, this innovative MCDM model contributes to a more accurate and objective analysis, enhancing the understanding of users' preferences and supporting informed decision-making in EV purchases

Mapping Ecotourism Potential in Bangladesh: The Integration of an Analytical Hierarchy Algorithm and Geospatial Data

The significance of ecotourism has been increasing due to its potential for biodiversity preservation, economic advancement, and the promotion of sustainability awareness. In this research, geospatial analysis and the Analytical Hierarchy Process (AHP) was employed to identify feasible ecotourism sites in Bangladesh. The study applied Geographical Information System–Remote Sensing (GIS-RS) parameters and weighted overlay techniques for selected ecotourism characteristics, such as natural attractiveness, topographic features, accessibility, proximity to facilities, and community characteristics. The study found that a significant proportion (around 44%) of Bangladesh’s land exhibits high potential for ecotourism. Cox’s Bazar, Chittagong, and Rangamati are particularly favorable ecotourism locations. However, some difficulties emerge in regions that are not easily reachable, such as mangrove forests, and in densely inhabited localities like Dhaka. The research also identified the ecological costs linked with ecotourism, such as the exhaustion of resources, the fragmentation of habitats, contamination, and the disruption of wildlife. The primary recommendations to address the adverse effects include educating the local populace, enforcing regulatory measures, implementing efficient waste management systems, enforcing a stringent code of conduct, providing economic incentives to the local communities, and addressing the issue of food security. The cartographically delineated potential zones have the potential to function as a navigational instrument for global travelers and facilitate the decision-making process of policymakers in the realm of sustainable land resource management in Bangladesh. This study enhances the understanding of the potential of ecotourism and offers valuable insights for advancing responsible and sustainable tourism practices within the nation

Ranking Agility Factors to Reliably Sustain a Green Industrial Supply Chain Using the Fuzzy Analytic Network Process and Ordinal Priority Approach

Suppliers can achieve high levels of supply chain sustainability by improving the related factors. An agile supply chain can support sustainability. Identifying and ranking agility factors in the SAIPA company in Iran to reach a sustainable and green supply chain is the primary purpose of this study. SAIPA is an automotive company with an extensive supply chain. The data were quantitative, and the collection was completed by reviewing the literature and questioning experts. The FANP and the OPA methods were the tools used to analyze the data. These methods are proper for facing multiple-criteria decision-making problems, as in the case of this paper. We first identified the factors (capabilities, enablers, and attributes) using a literature review. After that, we gathered the data for ranking analysis by collecting the opinions of SAIPA’s organizational experts using a pairwise comparison questionnaire for the FANP and a prioritizing list for the OPA. Both methods showed that “Quickness” is the capability with the highest priority. “Customer Sensitivity” was the most critical enabler, and “Accurate customer-based measures” was the most significant attribute of the FANP analysis. The OPA results showed that “Information Management” was the first enabler, and “Efficient funds transfer” took first place among all the attributes. Managers should pay more attention to these factors to develop agile supply chains in the SAIPA company. The results also showed that the methods proposed for multi-attribute decision-making problems like the FANP have shortcomings, such as difficulties completing the pairwise comparison matrix due to burdensome data collection in cases similar to the one in this study with many factors

Hard dimensions evaluation in sustainable supply chain management for environmentally adaptive and mitigated adverse eco‐effect environmental policies

In the oil and gas industry, adopting policies that can reduce the negative environmental effect is vital. Environmentally Sustainable Supply Chain Management (ESSCM) is an approach to carrying out Supply Chain Management (SCM) in an eco‐friendly manner and according to environmental requirements. There are different environmental policies that companies can apply based on their resource availability. Therefore, this study aims to evaluate the impact of hard dimensions on Environmentally Adaptive (EA) and Mitigated Adverse Eco‐Effect (MAE) policies in the oil and gas industry. To rank the data, Bayesian Best‐Worst Method (BWM) and Ordinal Priority Approach (OPA) have been applied. Cause‐and‐effect relationships are then calculated by employing the Decision‐Making Trial and Evaluation Laboratory (DEMATEL) technique. The results indicate that the ranking of the hard dimensions varies based on the companies' business policies and their new product/technology development projects. In other words, the findings of this research demonstrate that ‘innovation’ is the crucial dimension in companies that are focussed on developing eco‐friendly products while ‘technologies for cleaner production’ is the most important dimension in the companies attempting to reduce destructive consequences on the environment. In both types of the company policies, ‘lean manufacturing’, ‘total quality management’, and ‘institutional pressures’ are the key dimensions for a successful implementation of ESSCM while the least important dimensions include ‘supplier relationship management’, ‘green purchasing’, and ‘green logistics’. The findings of this research can assist the decision‐makers in the oil and gas sector in prioritising and identifying the interrelationship of the dimensions that significantly impact the ESSCM

Phyx.io: Expert-Based Decision Making for the Selection of At-Home Rehabilitation Solutions for Active and Healthy Aging

While the importance of physical activity in older adults is beyond doubt, there are significant barriers limiting the access of older adults to physical exercise. Existing technologies to support physical activity in older adults show that, despite their positive impacts on health and well-being, there is in general a lack of engagement due to the existing reluctance to the use of technology. Usefulness and usability are two major factors for user acceptance along with others, such as cost, privacy, equipment and maintenance requirements, support, etc. Nevertheless, the extent to which each factor impacts user acceptance remains unclear. Furthermore, other stakeholders, besides the end users, should be considered in the decision-making process to develop such technologies, including caregivers, therapists and technology providers. In this paper, and in the context of physical rehabilitation and exercise at home, four different alternatives with incremental characteristics have been defined and considered: a software-based platform for physical rehabilitation and exercise (Alternative 1), the same software platform with a conventional RGB camera and no exercise supervision (Alternative 2), the same software platform with a convention RGB camera and exercise supervision (Alternative 3) and finally, the same software platform with a depth camera and exercise supervision (Alternative 4). A multiple attribute decision-making methodology, based on the ordinal priority approach (OPA) method, is then applied using a group of experts, including end users, therapists and developers to rank the best alternative. The attributes considered in this method have been usefulness, cost, ease of use, ease of technical development, ease of maintenance and privacy, concluding that Alternative 3 has been ranked as the most appropriate.Si bien la importancia de la actividad física en los adultos mayores está fuera de toda duda, existen importantes barreras que limitan el acceso de los adultos mayores al ejercicio físico. Las tecnologías existentes para apoyar la actividad física en adultos mayores muestran que, a pesar de sus impactos positivos en la salud y el bienestar, en general existe una falta de compromiso debido a la renuencia existente al uso de la tecnología. La utilidad y la facilidad de uso son dos factores principales para la aceptación del usuario junto con otros, como el costo, la privacidad, los requisitos de equipo y mantenimiento, soporte, etc. Sin embargo, la medida en que cada factor afecta la aceptación del usuario sigue sin estar clara. Además, otras partes interesadas, además de los usuarios finales, deben ser consideradas en el proceso de toma de decisiones para desarrollar dichas tecnologías, incluidos los cuidadores, terapeutas y proveedores de tecnología. En este trabajo, y en el contexto de la rehabilitación física y el ejercicio en el hogar, se han definido y considerado cuatro alternativas diferentes con características incrementales: una plataforma de software para rehabilitación física y ejercicio (Alternativa 1), la misma plataforma de software con un Cámara RGB y sin supervisión de ejercicios (Alternativa 2), la misma plataforma de software con cámara RGB convencional y supervisión de ejercicios (Alternativa 3) y finalmente, la misma plataforma de software con cámara de profundidad y supervisión de ejercicios (Alternativa 4). Luego se aplica una metodología de toma de decisiones de múltiples atributos, basada en el método de enfoque de prioridad ordinal (OPA), utilizando un grupo de expertos, incluidos usuarios finales, terapeutas y desarrolladores para clasificar la mejor alternativa. Los atributos considerados en este método han sido utilidad, costo

Approaching Dynamic PSA within CANDU 6 NPP

The outline of this dissertation is going to present the applications that are the subject of the work and also the lay down of work content. Chapter 1 reviews the conventional PSA main concepts, summarizes a short introduction history of Dynamic PSA (DPSA) and presents a non-exhaustive DPSA state-of-the-art with the recent and future developments. Chapter 2 presents the first application of the thesis, which is actually an introduction in the context of the Integrated Dynamic Decision Analysis (IDDA) code, that represents the main tool used in the attempt of approaching the Dynamic PSA. Starting from a description that reflects the level of knowledge about the system, IDDA code is able to develop all the scenarios of events compatible with the description received, from both points of view: either logical construction, or probabilistic coherence. By describing the system configuration and operation in a logically consistent manner, all the information is worked out by the code and is made available to the analyst as results in terms of system unavailability, minimal cut sets, uncertainty associated. The code allows also the association of different consequences that could be of interest for the analyst. The consequences could be of any type, such as economical, equipment outage time, etc.; for instance it can be considered an outage time for certain components of the system and then is calculated the “expected risk”. The association of consequences provides the inputs for a good decision making process. Chapter 3 represents the core applications of the present work. The applications purpose is the coupling between the logic probabilistics of the system or plant and associated phenomenology of primary heat transport system of a generic CANDU 6 NPP. First application is the coupling between the logic-probabilistic model of EWS system and associated phenomenology of primary heat transport system of CANDU 6 NPP. The considered plant transient is the total Loss of Main Feed-water with or without the coincident failure of the Emergency Water Supply System. The second application is considering the CANDU 6 Station Blackout as plant transient-consequential condition, moreover the loss of all AC power sources existing on the site. The transient scenarios development consider the possibility to recover the offsite grid and the use of mobile diesel generators in order to mitigate the accident consequences. The purpose is to challenge the plant design and response and to check if the plant conditions of a severe accident are reached. The plant response is challenged for short and long periods of time. The IDDA code allows interfacing the logic-probabilistic model of the system with the plant response in time, therefore with the evolution in time of the plant process variables. This allows raising sequences of possible events related in cause-consequence reasoning, each one giving place to a scenario with its development and its consequences. Therefore this allows acquiring the knowledge not only of which sequences of events are taking place, but also of the real environment in which they are taking place. Associating the system sequences that lead to system unavailability on demand with the resulting phenomenology proves to be a useful tool for the decision making process, both in the design phase and for the entire power plant life time. Chapter 4 presents future possible applications that could be developed with the present Dynamic PSA approach. A particular application could be the optimization or development of robust plant emergency operating procedures. In fact it consists in the coupling between the logic-probabilistics of the plant configurations corresponding to the Emergency Operating Procedure (EOP) and the associated phenomenology of the primary heat transport systems with the consideration for the plant safety systems. The application could highlight those situations where the plant fails either because of hardware failures or system dynamics and furthermore to reveal those situations where changing of the hardware states brings the process variables of the system state out of the system domain. A timeline course should be created for the process variables characterizing the plant state and that should reveal the time windows that operators have at disposition for intervention, in order to avoid potentially catastrophic conditions. Some week points in the EOP could be identified and then resolutions to be provided for their improvement, on the basis of sensitivity analyses. Chapter 5 presents the conclusions and the insights of the work and outlines possible improvements in terms of the present methodology proposed

A novel multi-criteria group decision-making approach using aggregation operators and weight determination method for supplier selection problem in hesitant Pythagorean fuzzy environment

Uncertainty is an important factor in the decision-making process. Hesitant Pythagorean fuzzy sets (HPFS), a combination of Pythagorean and hesitant fuzzy sets, proved as a significant tool to handle uncertainty. Well-defined operational laws and attribute weights play an important role in decision-making. Thus, the paper aims to develop new Trigonometric Operational Laws, a weight determination method, and a novel score function for group decision-making (GDM) problems in the HPF environment. The approach is presented in three phases. The first phase defines new operational laws with sine trigonometric function incorporating its special properties like periodicity, symmetricity, and restricted range hence compared with previously defined aggregation operators they are more likely to satisfy the decision maker preferences. Properties of trigonometric operational laws (TOL) are studied and various aggregation operators are defined. To measure the relationship between arguments, the operators are combined with the Generalized Heronian Mean operator. The flexibility of operators is increased by the use of a real parameter λ to express the risk preference of experts. The second phase defines a novel weight determination method, which separately considers the membership and non-membership degrees hence reducing the information loss and the third phase conquers the shortcomings of previously defined score functions by defining a novel score function in HPFS. To further increase the flexibility of defined operators they are extended in the environment with unknown or incomplete attribute weights. The effectiveness of the GDM model is verified with the help of a supplier selection problem. A detailed comparative analysis demonstrates the superiority, and sensitivity analysis verifies the stability of the proposed approach

Offshore wind farm site selection in Norway : using a fuzzy trigonometric weighted assessment model

Maximising the energy potential of offshore wind farms requires an in-depth assessment of technological, economic, sociopolitical, and environmental aspects. Given the large economic impact of large-scale projects, a robust site selection procedure is critical for limiting financial risks while supporting informed investments. This research uncovers a novel and multidisciplinary approach for boosting the efficacy of Norwegian and global offshore wind farm siting investments. The proposed method uses a two-stage fuzzy mathematical model that considers technical, economic, logistical, and environmental factors. It combines the Ordinal Priority Approach (F-OPA) and Trigonometric Weighted Assessment (TRWA) technique by using an in-depth techno-economic assessment. An alternative reactive power compensation model, power loss calculations, and associated techno-economic analysis were performed for the investigated offshore wind farm locations. Furthermore, the energy economic calculations are carried out to provide support for the proposed decision-making framework. The proposed methodology was tested through a case study, focusing on ranking Norwegian offshore wind farm sites selected from potential locations announced by The Norwegian Water Resources and Energy Directorate (NVE). Within the Norwegian offshore wind farm sites, the approach demonstrated a versatile and efficient decision-making process at both individual and collective levels, identifying the Sandskallen-Sørøya Nord project as a pivotal investment priority and providing valuable managerial insights to enhance Norway’s offshore wind initiatives. The model’s stability was affirmed through a sensitivity analysis, underscoring its potential to enhance renewable energy policy and decision-making globally

Rough sets based Ordinal Priority Approach to evaluate sustainable development goals (SDGs) for sustainable mining

The Sustainable Development Goals (SDGs) have been adopted by countries and companies, including mining companies around the world. The aim of this study is to investigate the degree of importance of the seventeen sustainable development goals (SDGs) on sustainable mining using a rough sets based decision making approach. This novel approach consists of three consecutive stages, namely a questionnaire (survey), data analyses, and SDGs classification. Firstly, a survey is conducted to receive a response from internationally experts across different countries. Each participant is asked to evaluate the importance of each SDG. Secondly, the analyses are carried out to make a distinction among groups of participants who respond similarly and discover viewpoints from the industry, academia, and non-governmental organizations. Finally, the degree of importance of each SDG for sustainable mining is found using a novel decision making approach including Ordinal Priority Approach (OPA) based on rough sets. The survey of the results indicated that for all the participants of the survey, independently of their background, the most important SDG for sustainable mining was “SDG8: Decent work and economic growth”, while the one perceived as the least important was “SDG14: Life below water”. The main objective of SDG8 is to promote economic growth through job opportunities and decent work for all. This in turn leads to a more sustainable, long-term economic growth. While all SDGs play an important role, the proposed rough sets based decision making method provided a rational and objective evaluation performance of their perceived priority in the mining sector