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The influence of Acrylate Styrene Acrylonitrile (ASA) and ASA/nanosilica (ASA/Si) additives was investigated by using a dynamic shear rheometer (DSR). Firstly, an ASA polymer was blended with the virgin asphalt binder at two different concentrations (3% ASA and 5% ASA). After observing that 5% ASA was the optimum concentration for modification, nanosilica particles were further incorporated into the 5% ASA-modified asphalt binder with two different percentages (5% ASA 3%Si; 5% ASA 5%Si). Frequency sweep tests were conducted across various frequencies at elevated temperatures. The experimental outcomes were analyzed using master curves, rutting, and fatigue resistance parameter plots. Additionally, to provide a more holistic analysis, two different multicriteria decision analysis (MCDA) techniques, namely the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) and the Technique for the Order of Preference by a Similarity to Ideal Solution (TOPSIS), were conducted to identify the best-performing asphalt binder by considering three different parameters: workability, performance under different conditions, and cost. The frequency sweep tests showed that the 5% ASA 5%Si asphalt worked best in terms of resistance to rutting. On the other hand, the virgin binder performed better than all modified binders when it failed to resist fatigue. On the other hand, the PROMETHEE analysis identified the 5% ASA-modified asphalt binder as the optimal choice, while the TOPSIS analysis determined that the 5% ASA 3%Si-modified binder provided the best performance. The differences between the experimental results and the MCDA were due to using more than one evaluation parameter and looking at how well the asphalt binder worked at different temperature ranges at the same time. [ABSTRACT FROM AUTHOR]

In today's competitive environment, multi-branch companies allocate their stores with the aim of expanding their territorial coverage to attract new customers and increase their market share. Consumer satisfaction surveys either produce global performance results or they are not able to differentiate consumer perceptions using location analytics. This research develops a novel framework to assist multi-branch companies in mapping the consumer satisfaction performance of their stores, expanding conventional customer relationship management to the spatial context. The framework developed proposes a decision model that combines the Group Decision Support extension of the PROMETHEE and CRITIC methods in a GIS environment to generate satisfaction performance mappings. The developed decision-making framework converts consumer responses into satisfaction performance maps, allowing the company's stores and their competitors to be evaluated. Moreover, it provides insight into the potential opportunities and threats for each store. The performance of the proposed framework is highlighted through a case study involving a multi-branch coffeehouse company in a Greek city. Finally, a tool developed to assist the computational part of the framework is presented. [ABSTRACT FROM AUTHOR]

Since Kraljic's strategic matrix was applied to supply chain management, classification of items, suppliers, and customers has become of increasing interest to research and companies. The aim of this research is to develop an easily interpretable multicriteria classification matrix method and validate it in real-world scenarios with a robustness analysis. This method assigns alternatives to one of four classes defined by critical dimensions that integrate several evaluation criteria. Initially, a global search pre-classifies the alternatives using the PROMETHEE net flows. Then, two local searches are carried out that make use of the discriminant properties of the net flow signs to improve the quality of the assignments. This approach is specifically applied to pre-classified alternatives near the boundary between two or more categories. The method has been validated by segmenting thousands of customers. Four customer segments were identified: strategic, collaborative, transactional, and non-preferred. A comparison was made between the results and those derived from an alternative method. Through an extensive sensitivity analysis, the proposed method was shown to be robust to parameter variation, highlighting its reliability in real dynamic contexts. The method provides valuable, easily interpretable information, which constitutes the basis for developing personalised strategies to enhance customer relationship management. [ABSTRACT FROM AUTHOR]

The project was conducted in the Ashigua páramo, Mulaló, Latacunga, Cotopaxi province. Its objective was to develop a composite environmental sustainability indicator for the conservation of the páramo. Neutrosophic logic and the PROMETHEE TODIM method were used to select and evaluate sub-indicators in a context of uncertain and complex environmental data. Neutrosophic logic facilitated the management of ambiguities and contradictions in the data. The findings highlighted the relevance of sub-indicators linked to carbon storage and ecological productivity. Indicators of regulatory compliance and sustainable management were evaluated, emphasizing the importance of adjusting environmental policies to regulations and social expectations. This study introduced a novel methodological approach to environmental assessment, providing valuable insights for policy development and effective management of natural resources and ecosystems. [ABSTRACT FROM AUTHOR]

The goal of this study was to create a fermented probiotic fruit puree for lactose‐intolerant people, vegetarians, and infants over 6 months old. Fermented fruit purees were developed using apples, peaches, and bananas with lactic acid bacteria (LAB) strains: Lactobacillus plantarum subsp. plantarum (S5), Lactobacillus fermentum strain w8 (S10), and Lactobacillus pentosus strain ml104 (S14). Different fruit puree formulations were produced using three strains, two inoculation ratios (4% and 5%), and two fermentation durations (24 and 48 h). The physicochemical parameters (pH, total soluble solids, and color), total phenols content (TPC), total antioxidant capacity, bacterial viability, volatile aroma profile (VAP), and individual phenolic compound profile of fruit puree fermented for both 24 and 48 h were compared with the unfermented (control) purees. The results of VAP were evaluated via PROMETHEE and cluster analysis. Time of fermentation and bacterial cultures at varied concentrations improved color values of samples (L*, a*, and b*) compared to controls. The level of bioactive compounds in several samples (S10 and S14) decreased after fermentation in contrast to S5 samples. The bacterial population in the samples ranged from ∼7.00 to 9.50 log CFU/g after 48‐h fermentation. The fruit puree samples exhibited the presence of two different phenolic compounds and a total of 17 distinct volatile aroma compounds. The control sample scored highest for aromatic components in PROMETHEE, while S14‐II was the most unique sample in cluster analysis. In conclusion, fermented probiotic fruit puree shown high promise as a carrier for live probiotics, and the fermentation process boosted the nutritional content of the fruit puree. [ABSTRACT FROM AUTHOR]

Copyright of Verimlilik Dergisi is the property of Verimlilik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Amaç: Günümüz rekabetçi ekonomisinde firmaların ayakta kalabilmeleri için dijital olgunluk seviyelerinin değerlendirilmesi önemlidir. Bu çalışmada, Türk savunma sanayii kapsamındaki dört firmanın dijital olgunluk düzeyleri incelenmiştir. Değerlendirme, firmaların eksikliklerini belirleyip çözümler sunarak rekabet avantajı, sürdürülebilirlik ve verimlilik sağlamayı hedeflemektedir.Yöntem: Problemde kullanılan kriterlerin ağırlıklandırılmasında Analitik Hiyerarşi Süreci (AHP) yöntemi kullanılmıştır. Ardından alternatif seçimlerinde ise çok kriterli karar verme yöntemlerinden Technique for Order Preference By Similarity To Ideal Solution (TOPSIS) ve Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) yöntemleri tercih edilmiştir.Bulgular: Dijital olgunluk, akıllı üretim sistemleriyle verimliliği artırma kapasitesi olarak tanımlanmıştır. AHP ile ağırlıklandırılan kriterler arasında “Endüstri 4.0 Teknolojileri Kullanma Süreçleri” en öncelikli kriter olarak belirlenmiştir. TOPSIS ve PROMETHEE yöntemleriyle yapılan sıralamalarda 1. Firma en üst sırada yer almıştır. Çalışma, firmaların dijital dönüşüm süreçlerindeki güçlü ve zayıf yönlerini ortaya koymuştur. Gelecek araştırmalar için sektörel analizler ve yeni yöntemler önerilmektedir.Özgünlük: Bu çalışma, AHP, TOPSIS ve PROMETHEE yöntemlerini kullanarak Türk savunma sanayiindeki firmaların dijital olgunluk seviyelerini analiz eden özgün bir metodolojik yaklaşım sunmaktadır. Analiz, sektördeki firmaların dijital dönüşüm stratejilerini optimize etmelerine katkı sağlamaktadır.

Timber industries make an essential contribution to economies worldwide, while the sustainable supply of timber generates revenue, supports employment, and contributes to economic activity. The strategic choice of wood species using specific criteria can have substantial economic outcomes for the timber industry in Greece. This study assessed the suitability of hardwood species most commonly used by Greek timber industries. The assessment was conducted with the use of a Multiple-Criteria Decision Analysis approach, taking into consideration specific criteria that affect the quality of timber. According to the findings, walnut was the optimal alternative that outranked the other examined species. Chestnut, oak, beech, ash, and hornbeam also achieved positive scores, and therefore, they are also acceptable alternatives as broadleaved species suitable for furniture manufacturing and sawn timber production. Greek timber industries can enhance their products’ value and market appeal by focusing on species that meet high-quality standards and consumer preferences.

This article is devoted to the assessment of the country’s sustainable cyberspace strategy by comparing the cyber security strategies of those countries that are economically developed and use advanced information and communication technologies. Based on the components of the National Cyber Security Index, a calculation was made for 10 countries, which made it possible to monitor the effectiveness of their cyber strategies and identify their shortcomings. The calculation is made for the years 2018 and 2021. During this period, no significant critical changes form abnormal indicators, but it is possible to reflect a particular trend. Application of the PROMETHEE method (I and II) and the formation of net flows, determination of importance and comparison of alternatives allowed to carry out an in-depth analysis of various aspects of cyber security, such as protection measures, response to cyber threats and general resistance to cyber-attacks. It is determined that Belgium and Lithuania are the most resistant to threats from cyber-attacks and in the fight against money laundering among the countries considered, as they are rapidly developing and implementing new measures. Their indicators increased by 0.1 values in 2021 compared to 2018. According to the calculations, Great Britain is the most conservative in implementing certain strategies, and its indicators remained at the level of 0-0.2 according to various criteria for the years studied. Most countries improve their indicators by a total of 0.2 values, which reflects their development. Ukraine tends to decrease some indicators by 0.1 value; some are at the same level. The regulatory framework's introduction rate in the cyber security field increases. It shows that Ukraine has many rapidly changing risks, but is trying to achieve flexibility in responding to them. The research findings identify each country’s cybersecurity strengths and weaknesses, as well as potential risks and vulnerabilities. Thanks to this analysis, recommendations are made for developing and implementing effective cyber security strategies, both at the national and international levels. The study contributes to the understanding of the complexity of modern cyber threats. It emphasizes the need for continuous improvement and adaptation of protection measures to ensure the stability and security of financial and information systems in a global digital environment.

Polycentricity is a multiscalar concept referring to the interconnections of neighboring spatial areas in search of synergies. More specifically, urban polycentricity has lately gained increasing momentum in academic research and strategic planning as urban polycentric structures could stimulate urban and regional performance in a sustainable way. Architectural heritage, with its connotative meanings, is among the indicators of incorporation in polycentric networking. The present paper investigates the challenges of implementing urban polycentricity methodological approaches to highlight new polycentric networks based on built architectural heritage. In this study, appointed architectural assets are considered as nodes of the potential networks. As a new research strand, the MCDA PROMETHEE method is applied to compile and assemble all indicators (namely, rank size and node hierarchy, accessibility, transportation, and digital promotion). The ultimate research goal is to build a new polycentricity index as an innovative methodological tool to highlight polycentric networking synergies on interurban and intraregional scales. The region of Thrace in Northern Greece is chosen to apply the proposed methodology. Research on ways to couple polycentricity and PROMETHEE methods is limited, and thus, the proposed methodological approach is expected to contribute to the field of urban and regional strategies for researchers and practitioners. [ABSTRACT FROM AUTHOR]

The aim of this research is to develop a robust multicriteria method to classify suppliers into ordered categories and its validation in real contexts. The proposed technique is based on a property of net flows of the PROMETHEE method and uses global and local search concepts, which are common in the optimisation field. The results obtained are compared to those from the most cited sorting algorithm, and an empirical validation and sensitivity analysis is performed using real supplier evaluation data. Furthermore, it does not require additional information from decision‐makers as other sorting algorithms do for assigning incomparable or indifferent alternatives to groups. An extension of the silhouette concept from data mining is also contributed to measure the quality of ordered classes. Both contributions are easy to apply and integrate into decision support systems for automated decisions in the supply chain management. Finally, this practical approach is also useful to classify customers and any type of alternatives or actions into ordered categories, which have an increasing number of real applications. [ABSTRACT FROM AUTHOR]

Logistics and distribution centres are essential to the supply chains of many manufacturing and logistics companies. Efficiently locating logistic centres involves thorough search for optimal place, prioritizing proximity to suppliers and minimizing costs. Companies' management often solves the location problem of new halls, mostly to minimise the associated costs. Such a problem is solved in the automotive industry as part of the launch of a new international project. The key factor for the decision of where to locate the logistics centre is the location of the suppliers, since material deliveries generate a large part of the project costs. The aim of this study is to define a methodology for the location of the logistics centre, considering several alternative locations and relevant criteria. The location alternatives and criteria are defined in terms of minimising project costs and sustainability elements. The problem is solved using the multi-criteria decision-making approach. First, the AHP method is used to assign weights to the criteria. Then the PROMETHEE method is applied to find a suitable location for the logistics centre and to perform a thorough sensitivity analysis. The sensitivity analysis is focused on the impact of values of weights on the solution. Consequently, the analysis proves the correctness of the selected alternative. Based on the case study, a general methodology for locating a logistics centre is proposed. [ABSTRACT FROM AUTHOR]

The current economic and political crisis has brought about a change in the environment in which non-governmental development organisations (NGDOs) have traditionally operated. This change can be summed up as a reduction in the funds they receive and an increase in the population they must serve. The need then arises to have mechanisms that allow an analysis of the good work performed by the NGDOs. Knowing the efficiency of the NGDOs in the management of their previous projects can contribute towards improving their future achievements. The aim of this research is to establish some objective indicators that allow an evaluation of the efficiency of these organisations. Firstly, a detailed analysis of the regulation of the three agencies is conducted (Spanish-AECID, European-EuropeAid, and American-USAID). This allows us to synthesise the indicators of good performance of the NGDO based on the study of the eligibility criteria of public donors. The research concludes with the study of the efficiency following the Promethee Approach. Our results reveal that 44.6% of the NGDOs (33 out of the 74 studied) operate inefficiently, compared to 29.7%, which are efficient. [ABSTRACT FROM AUTHOR]

The structural design of prestressed arched trusses presents a complex challenge due to the need to balance multiple conflicting objectives such as structural performance, weight, and constructability. This complexity is further compounded by the interdependent nature of the structural elements, which necessitates a comprehensive optimization approach. Addressing this challenge is crucial for advancing construction practices and improving the efficiency and safety of structural designs. The integration of advanced optimization algorithms and decision-making techniques offers a promising avenue for enhancing the design process of prestressed arched trusses. This study proposes the use of three advanced multi-objective optimization algorithms: NSGA-III, CTAEA, and SMS-EMOA, to optimize the structural design of prestressed arched trusses. The performance of these algorithms was evaluated using generational distance and inverted generational distance metrics. Additionally, the non-dominated optimal designs generated by these algorithms were assessed and ranked using multiple multi-criteria decision-making techniques, including SAW, FUCA, TOPSIS, PROMETHEE, and VIKOR. This approach allowed for a robust comparison of the algorithms and provided insights into their effectiveness in balancing the different design objectives. The results of the study indicated that NSGA-III exhibited superior performance with a GD value of 0.215, reflecting a closer proximity of its solutions to the Pareto front, and an IGD value of 0.329, indicating a well-distributed set of solutions across the Pareto front. In comparison, CTAEA and SMS-EMOA showed higher GD values of 0.326 and 0.436, respectively, suggesting less convergence to the Pareto front. However, SMS-EMOA demonstrated a balanced performance in terms of constructability and structural weight, with an IGD value of 0.434. The statistical significance of these differences was confirmed by the Kruskal–Wallis test, with p-values of 2.50 × 10 − 15 for GD and 5.15 × 10 − 06 for IGD. These findings underscore the advantages and limitations of each algorithm, providing valuable insights for future applications in structural optimization. [ABSTRACT FROM AUTHOR]

This scientific study examines the evaluation of photovoltaic power generation projects through the application of multi-criteria decision analysis methods. Two groups of large-scale grid-connected PV power generation system projects with a nominal power of 50 MW and 500 MW respectively were analyzed and evaluated. These systems were designed to be installed in the same wider geographical area in northern Greece, but they were differentiated in the part of the PV circuit. Twelve systems were analyzed in which either monocrystalline silicon panels or poly-crystalline silicon panels or bifacial photovoltaic panels were to be installed. In these systems either central photovoltaic inverters or photovoltaic string inverters were considered for installation. The following criteria were used to evaluate the investment in these projects. These criteria were related to the profitability, the financial cost, the technical level, and the electrical energy production of the systems and these were the initial investment cost, the operation and maintenance cost, the levelized cost of electricity, the net present value, the internal rate of return, the capital recovery or payback period, the technical level of the photovoltaic circuit, the technical maturity of the photovoltaic circuit, and the annual electricity production. The evaluation of these criteria was initially conducted with fixed weighting coefficients followed by a sensitivity analysis of these weighting coefficients. The results of the evaluation using the PROMETHEE, AHP and TOPSIS multi-criteria decision analysis methods showed that the PV power generation systems which should be preferred are those with increased nominal power, where monocrystalline silicon technology panels are employed following the central inverter topology.

On a global scale, flooding is the most devastating natural hazard with an increasingly negative impact on humans. It is necessary to accurately detect flood-prone areas. This research introduces and evaluates the Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) integrated with GIS in the field of flood susceptibility in comparison with two conventional multi-criteria decision analysis (MCDA) methods: analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The Spercheios river basin in Greece, which is a highly susceptible area, was selected as a case study. The application of these approaches and the completion of the study requires the creation of a geospatial database consisting of eight flood conditioning factors (elevation, slope, NDVI, TWI, geology, LULC, distance to river network, rainfall) and a flood inventory of flood (564 sites) and non-flood locations for validation. The weighting of the factors is based on the AHP method. The output values were imported into GIS and interpolated to map the flood susceptibility zones. The models were evaluated by area under the curve (AUC) and the statistical metrics of accuracy, root mean squared error (RMSE), and frequency ratio (FR). The PROMETHEE model is proven to be the most efficient with AUC = 97.21%. Statistical metrics confirm the superiority of PROMETHEE with 87.54% accuracy and 0.12 RMSE. The output maps revealed that the regions most prone to flooding are arable land in lowland areas with low gradients and quaternary formations. Very high susceptible zone covers approximately 15.00–19.50% of the total area and have the greatest FR values. The susceptibility maps need to be considered in the preparation of a flood risk management plan and utilized as a tool to mitigate the adverse impacts of floods. [ABSTRACT FROM AUTHOR]

The decision-making process regarding the allocation of professor positions is a recurring theme in higher education institutions. The study shows a model of allocation of teaching positions based on a hybrid methodology AHP-PROMETHEE, proposed for a higher education institution with distribution of vacancies in departments. Where, through the case study, it was possible to determine, through a scientific technique, the appropriate allocation of places, presenting as a result the department in which the vacancy will be allocated. For this purpose, the AHP was used to define the weights of the analyzed criteria and the PROMETHEE to select the department that will receive the teaching post. The work also compares the result presented by the proposed method with the solutions proposed by the model used by the analyzed institution and the MEC/Andifes model, in addition to demonstrating the advantages of using the AHP-PROMETHEE technique to solve the problem. [ABSTRACT FROM AUTHOR]

In recent years, the concept of entrepreneurial and innovative universities has gained widespread prominence. Many universities have been paying more attention to being entrepreneurial and innovative by improving their organizational systems, advancing their infrastructure, and increasing financial support. Since numerous criteria with different weights exist, ranking universities based on entrepreneurial and innovative performance can be considered a multi-criteria decision-making (MCDM) problem. This article aims to investigate how different multi-criteria decision-making methods with different criterion weights can affect university rankings and to highlight the reasons that contribute to these differences. In this scope, Grey Relational Analysis (GRA) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods were used to rank and compare the universities in Türkiye according to the 2022 Entrepreneur and Innovative University Index (EIUI). In addition to the current weights of each EIUI dimension, entropy-based weights and equal weights were used in MCDM methods. Three ranking approaches with varying weights provided different rankings for universities. The effect of criterion weights was found to be more important in the ranking difference than the method used. The ranks for universities coded U1 and U2 as the most entrepreneurial and innovative universities remained the same. In addition, the performance of each university according to each dimension was evaluated graphically using the GAIA plane to enable them to identify areas for improvement in their rankings. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon, which affects in several ways different regions all around the world, beyond the rise in global temperature. Among the different climate change issues, the management of transport infrastructures is crucial. Particularly, their vulnerability against changes in climatic conditions should be assessed. Vulnerability indicators are based on the IPCC concept of vulnerability and can be defined as a function of Climate Exposure, Sensitivity, and Adaptive Capacity. These dimensions need to be addressed during the assessment making and can be modelled as a Multiple Criteria Decision Analysis (MCDA) problem. This study proposes an integrated approach of several MCDA methods as a possible tool for ranking the climate change vulnerability of coastal roads in Malta. The application covers six coastal roads in the islands of Malta, classified by three different MCDA methods. The results indicate that the proposed approach can produce a consistent ranking of the climate change vulnerability of coastal roads. The study provides policy and decision-makers with a definition of a coastal road, an inventory of such roads, a list of climate change impacts, and a mathematical model incorporating climate change vulnerability indicators. The model can be used to prioritize investment and plan climate change adaptation strategies for infrastructural works on coastal roads. [ABSTRACT FROM AUTHOR]

Heart failure is a progressive disease that leads to high mortality rates if left untreated, and inotropes are a class of drugs used to treat a type of heart failure where patients have reduced ejection fraction (HFrEF). This study aims to utilize the Fuzzy-Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE), an effectively used multi-criteria decision making (MCDM) technique. To analyze the characteristics of the most often used inotropes for acute HFrEF and chronic HFrEF, we use the same parameters set with distinct importance factors and aims for each property and, therefore, mathematically demonstrate the strengths and weaknesses of each inotrope alternative. As a result, a detailed ranking list for each HFrEF class was obtained, with supplementary information on how each parameter contributed to the ranking of each inotrope. From these results, it was concluded that the F-PROMETHEE method is applicable for evaluating the risks and benefits of various inotropes to determine a starting point for treating an average patient when making a quick decision without complete patient data. As demonstrated in this study, it is possible to easily use the same data set and only change some preference parameters according to individual needs to produce patient-specific results. In this study, we showed that creating a decision-making system that mathematically assists clinical specialists with their decision-making process is feasible. [ABSTRACT FROM AUTHOR]

Ecotourism, aimed at appreciating and preserving biodiversity and natural ecosystems while providing economic and social benefits to local communities, faces complexity in management, requiring careful consideration to balance economic, social, and environmental aspects. Decision-making in ecotourism management involves various stakeholders, including government, NGOs, industry players, and local communities. CMC Tiga Warna in Indonesia is a highly potential ecotourism destination but poses challenges in environmental sustainability while meeting the economic and social needs of the local community. Thus, developing a decision support system (DSS) for sustainable community-based ecotourism management becomes crucial. This study aims to develop and implement a DSS based on priority actions, considering biodiversity, local community welfare, environmental and financial sustainability. Utilizing a community-based approach, the study engages local stakeholders and analyzes priority management actions across eight dimensions. Multi-criteria techniques like PROMETHEE will determine the best management actions to address challenges and opportunities for sustainable ecotourism management. The research contributes to sustainable management strategies for ecotourism in CMC Tiga Warna and provides a foundation for similar DSS development in other ecotourism contexts. It underscores the importance of holistic and sustainable ecotourism management for achieving economic development while conserving the environment, serving as a model for creating sustainable ecotourism environments worldwide. [ABSTRACT FROM AUTHOR]

This research carries out a comparative analysis of the Internal Market Orientation (IMO) to a sample of small and medium enterprise companies, which has been divided into nine groups based on their business sectors. Applying the statistical technique of structural equations, the coefficients of four IMO inputs in each business sector are obtained. Next, the PROMETHEE multicriteria technique is applied to obtain a composite indicator of the IMO implementation of each business sector. The value of the composite indicator together with the GAIA plane allow to distinguish the differences of the IMO profiles, their strengths and their weaknesses. The results show the divergences in the IMO inputs according to the sector, which is evidence that the business sector is a predictor of the IMO implementation of a company. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Engineering Research & Development (IJERAD) is the property of International Journal of Engineering Research & Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With an increasing focus on sustainable development and the reuse of disused infrastructure, there is a pressing need for effective decision-making methods. This study explored the use of the PROMETHEE method within a collaborative decision-making framework to assess the adaptive reuse options for a disused railway in Sicily, Italy. Using a participatory paradigm, the research actively involves stakeholders in the assessment process. The collaborative PROMETHEE approach acts as a tool for multi-criteria decision analysis, facilitating the comparison and prioritization of different reuse alternatives based on predefined criteria. The research highlights the effectiveness of PROMETHEE in streamlining decision-making processes for adaptive reuse efforts, particularly in the context of integrated conversions of abandoned railways. By combining multi-criteria decision analysis with collaborative methods, the study contributed to the formulation of sustainable and socially responsible strategies for the valorization of disused railway infrastructure. The results underline the importance of collaborative decision-making processes and the instrumental role of PROMETHEE in assisting stakeholders in evaluating and selecting adaptive reuse options for disused railways, thereby, in turn, promoting the sustainable development of these sites. [ABSTRACT FROM AUTHOR]

The advancement toward sustainable infrastructure presents complex multi-objective optimization (MOO) challenges. This paper expands the current understanding of design frameworks that balance cost, environmental impacts, social factors, and structural integrity. Integrating MOO with multi-criteria decision-making (MCDM), the study targets enhancements in life cycle sustainability for complex engineering projects using precast modular road frames. Three advanced evolutionary algorithms—NSGA-II, NSGA-III, and RVEA—are optimized and deployed to address sustainability objectives under performance constraints. The efficacy of these algorithms is gauged through a comparative analysis, and a robust MCDM approach is applied to nine non-dominated solutions, employing SAW, FUCA, TOPSIS, PROMETHEE, and VIKOR decision-making techniques. An entropy theory-based method ensures systematic, unbiased criteria weighting, augmenting the framework's capacity to pinpoint designs balancing life cycle sustainability. The results reveal that NSGA-III is the algorithm converging towards the most cost-effective solutions, surpassing NSGA-II and RVEA by 21.11% and 10.07%, respectively, while maintaining balanced environmental and social impacts. The RVEA achieves up to 15.94% greater environmental efficiency than its counterparts. The analysis of non-dominated solutions identifies the A 4 design, utilizing 35 MPa concrete and B500S steel, as the most sustainable alternative across 80% of decision-making algorithms. The ranking correlation coefficients above 0.94 demonstrate consistency among decision-making techniques, underscoring the robustness of the integrated MOO and MCDM framework. The results in this paper expand the understanding of the applicability of novel techniques for enhancing engineering practices and advocate for a comprehensive strategy that employs advanced MOO algorithms and MCDM to enhance sustainable infrastructure development. [ABSTRACT FROM AUTHOR]

In the current research work, AA7050 a marine aluminium alloy was reinforced with the nano-graphite particles, processed through the stir casting technique. The scanning electron microstructure reveals, that the nanoparticles were uniformly distributed over the matrix material and the hardness of the composites increased with a rise in the weight percentage of Gr particles owing to the Hall patch effect. The wear experiments were conducted by varying reinforcement, load, velocity, distance, and temperature, and the experimental runs were designed using the L25 orthogonal array, in which wear, coefficient of friction and worn surface hardness were recorded as a response. The wear resistance of the composites increases with a rise in the graphite content attributed to the formation of a mechanically mixed layer, the wear rate transfers from mild to severe, when there is shift in temperature from 100°C to 150°C. The worn surface hardness of the composites was higher than those of as-cast composites owing to the presence of Fe on the surface confirmed through the EDAX mapping. The composites were optimized using the modified PROMETHEE optimization technique and the results revealed that AA7050 reinforced with 8% Gr particles showed the best result and was recommended for the marine sector. [ABSTRACT FROM AUTHOR]

The recent PROMETHEE‐Scoring approach offers a method for generating cardinal scores through an outranking procedure utilizing Stochastic Multicriteria Acceptability and σ$$ \sigma $$–μ$$ \mu $$ analysis. In this paper, we illustrate some undesirable effects of this method and explore possible approaches to address them. First, we modify the original LP by inserting a new constraint that limits negative impacts caused by alternatives with low flow mean and standard deviation. Also, clustering is used to identify outliers in the decision matrix that may induce undesirable effects. A toy example demonstrates the issues and explores the proposed implementations. In addition, a numerical application is presented where a set of countries is ordered based on criteria from an economic freedom assessment. Both the numerical application and the toy example show that the propositions can improve the consistency of the results and prevent inconsistent outputs. The results include comparisons between the rank of alternatives when using purely the PROMETHEE‐Scoring method, the proposed improvements, and the expected results from SMAA‐PROMETHEE. [ABSTRACT FROM AUTHOR]

The highly dynamic nature of the real-world environment poses significant challenges for electric bus system operations (EBSOs), which are prone to serious accidents due to their complexity and a wide variety of risk factors. The accidents are often the result of ignoring the most serious risk sources because of a lack of comprehensive risk assessments. Therefore, this paper proposes an improved failure mode and effects analysis (FMEA) multicriteria group decision-making model to ensure the reliability and safety of EBSOs. First, an expert group is invited to evaluate the risk failure modes (FMs) of the EBSOs and transform them into a normal wiggly hesitant fuzzy set (NWHFS) form. Because the risk assessment process involves a large number of team members with different backgrounds, the experts are grouped based on scoring function values using the K-medoids clustering technique. Then, the evaluation values of the expert group are integrated using the normal hesitant fuzzy weighted geometric (NWHFWG) aggregation operator to obtain the final aggregation matrix, and the weights of the three criteria of occurrence (O), severity (S) and detection (D) are determined for each FM via the CCSD method. Finally, considering the cross-correlation between factors within the system, the relationships between FMs are analyzed, and their impact and importance are quantified using the gray correlation-based DEMATEL method, followed by the final ranking of the FMs using regret theory and the PROMETHEE II methodology to achieve a rational allocation of resources. The results are analyzed with sensitivity and comparative analyses to illustrate the superiority of the model. [ABSTRACT FROM AUTHOR]

Sustainable construction becomes a highly key topic in the construction sector owing to its benefits and advantages over economy, environment, and society. This study considers one such application of sustainable construction, rehabilitation of RC beams. Through such rehabilitation, it is possible to extend the life of existing concrete structures. A numerical analysis approach has been framed to study to this phenomenon. Total 10 criteria have been selected to evaluate the rehabilitation material alternatives on RC beams with ultra-high-performance concrete. 9 Alternative materials have been considered for rehabilitation of RC beams. DEMATEL-ANP and PROMETHEE has been used as a methodology in two phases, the first phase used DEMATEL-ANP to analyze the considered criteria and the second phase used PROMETHEE to evaluate the considered alternative materials based on the analyzed criteria. Finally, this study concludes with the effective rehabilitation material for RC beams with ultra-high-performance-concrete. The considered numerical framework can be adopted in various forms of similar or different applications. [ABSTRACT FROM AUTHOR]

The importance of public transportation service quality research is significantly increasing in recent years, it is the key to understanding and analyzing passengers' preferences. Different approaches are utilized to explore users' preferences however, dominantly these apply merely subjective scoring of the attributes and alternatives of the mobility. In this paper, we design a specific model for public transportation mode choice which is capable of integrating subjective scoring with scoring by objective measures such as distance or time. Owing to this purpose, we combine the outranking Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) as a method to evaluate passengers' preferences for tangible and intangible criteria with the fuzzy theory, and the Graphical Analysis for Interactive Aid (GAIA) plane to visualize the interactions between attributes as well as to test the robustness of the results via sensitivity analysis. The contribution of this paper is the constructed integrative method that is less subjective than the well-known models but also keeps the freedom of individual evaluators in expressing their preferences. Moreover, another significant issue of mode choice analysis is the group consideration, which is also refined in the new methodology by taking into account not only the mean of group preferences but also their range. A common characteristic of public surveys, the possible vague responses of the layman pattern is solved with the fuzzy approach to reduce the risk of uncertain scoring. The proposed model acts as a great base for the fuzzy inference system that can facilitate mode choice for passengers within a changing environment. The efficiency of the new methodology is demonstrated through a real-world case study of Budapest city, the obtained results are supporting underground mode service quality and highlighting its impact on citizens' behavior in favor of public transport. [ABSTRACT FROM AUTHOR]

This article is devoted to the assessment of the country's sustainable cyberspace strategy by comparing the cyber security strategies of those countries that are economically developed and use advanced information and communication technologies. Based on the components of the National Cyber Security Index, a calculation was made for 10 countries, which made it possible to monitor the effectiveness of their cyber strategies and identify their shortcomings. The calculation is made for the years 2018 and 2021. During this period, no significant critical changes form abnormal indicators, but it is possible to reflect a particular trend. Application of the PROMETHEE method (I and II) and the formation of net flows, determination of importance and comparison of alternatives allowed to carry out an in-depth analysis of various aspects of cyber security, such as protection measures, response to cyber threats and general resistance to cyber-attacks. It is determined that Belgium and Lithuania are the most resistant to threats from cyber-attacks and in the fight against money laundering among the countries considered, as they are rapidly developing and implementing new measures. Their indicators increased by 0.1 values in 2021 compared to 2018. According to the calculations, Great Britain is the most conservative in implementing certain strategies, and its indicators remained at the level of 0-0.2 according to various criteria for the years studied. Most countries improve their indicators by a total of 0.2 values, which reflects their development. Ukraine tends to decrease some indicators by 0.1 value; some are at the same level. The regulatory framework's introduction rate in the cyber security field increases. It shows that Ukraine has many rapidly changing risks, but is trying to achieve flexibility in responding to them. The research findings identify each country's cybersecurity strengths and weaknesses, as well as potential risks and vulnerabilities. Thanks to this analysis, recommendations are made for developing and implementing effective cyber security strategies, both at the national and international levels. The study contributes to the understanding of the complexity of modern cyber threats. It emphasizes the need for continuous improvement and adaptation of protection measures to ensure the stability and security of financial and information systems in a global digital environment. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to enable the analysts of reliability and safety systems to evaluate the risk and prioritize failure modes ideally to prefer measures for reducing the risk of undesired events. Design/methodology/approach: To address the constraints considered in the conventional failure mode and effects analysis (FMEA) method for criticality assessment, the authors propose a new hybrid model combining different multi-criteria decision-making (MCDM) methods. The analytical hierarchy process (AHP) is used to construct a criticality matrix and calculate the weights of different criteria based on five criticalities: personnel, equipment, time, cost and quality. In addition, a preference ranking organization method for enrichment evaluation (PROMETHEE) method is used to improve the prioritization of the failure modes. A comparative work in which the robust data envelopment analysis (RDEA)-FMEA approach was used to evaluate the validity and effectiveness of the suggested approach and simplify the comparative analysis. Findings: This work aims to highlight the real case study of the automotive parts industry. Using this analysis enables assessing the risk efficiently and gives an alternative ranking to that acquired by the traditional FMEA method. The obtained findings offer that combining of two multi-criteria decision approaches and integrating their outcomes allow for instilling confidence in decision-makers concerning the risk assessment and the ranking of the different failure modes. Originality/value: This research gives encouraging outcomes concerning the risk assessment and failure modes ranking in order to reduce the frequency of occurrence and gravity of the undesired events by handling different forms of uncertainty and divergent judgments of experts. [ABSTRACT FROM AUTHOR]

Existen dos grandes divisiones en las situaciones de toma de decisiones con múltiples obje­tivos: programación multiobjetivo, referido a variables continuas, y decisiones multicriterio discretas. El trabajo se centra en la problemática de las decisiones multicriterio discretas (DMD). Estos métodos son técnicas de apoyo para resolución de situaciones en las cuales se debe escoger una alternativa entre varias. El trabajo presenta un modelo de la escuela francesa –PROMETHEE–, que se centra en el cálculo de las preferencias de cada alternativa respecto a las otras en cada criterio y luego en forma conjunta. En una primera parte del trabajo se expone el método PROMETHEE en su versión clásica. Posteriormente se aclaran las posibles transiciones entre no preferencia y la preferencia completa. La última parte del trabajo propone una variante para el cálculo de la transición de modo de no agregar mayores subjetividades. Se contempla, además, el aspecto de la sensibilidad de la decisión sugerida. La categoría propuesta se fundamenta en que los métodos cuantitativos son herramientas de apoyo en el proceso decisorio y éste, a su vez, es una temática central en la gestión de todas las organizaciones, sean pequeñas o importantes.

Cultural tourism products refer to the special tourism products supported by cultural tourism resources and aimed at obtaining cultural impression and increasing intelligence. This study establishes a hybrid multi-criteria decision-making (MCDM) framework to solve the evaluation and pricing issues of cultural tourism products. In the proposed framework, picture fuzzy sets are adopted to thoroughly depict decision-making information with four independent functions. Simultaneously, a novel picture fuzzy numbers cross-entropy-based optimization model (PFN-CEBOM) is proposed to reveal the significance of decision-making attributes. The advanced PFN-CEBOM can get comprehensive criteria weights by covering both objective and subjective weight data in picture fuzzy environments. Then, the traditional preference ranking organization method for enrichment evaluations (PROMETHEE) is modified with picture fuzzy information to get non-compensatory decision-making results. And finally, the proposed method is applied to evaluate and pricing different cultural tourism products in China. Additionally, the availability and superiority of the proposed model are verified through sensitive and comparative analyses. Results evince that the proposed approach is valid for reasonable pricing of cultural tourism products and can serve as a promising instrument for tourism industries.

This paper addresses the imperative task of assessing and ranking cryptocurrencies, particularly pertinent in the context of the burgeoning popularity of public blockchains. The proliferation of available options necessitates a rigorous evaluation, prompting the formulation of a novel model grounded in both objective and subjective criteria. To contend with the challenge posed by the expanding landscape of public blockchains, ten discerning criteria are delineated, encompassing facets such as Technology, TPS, Market capitalization, GitHub fork, GitHub stars, Twitter followers, Twitter hashtags, trading volume, sentiment score, and the price range differential. Leveraging expert opinions, the pairwise impact of these criteria is ascertained, and the DEMATEL method is judiciously employed to derive their respective weights. Subsequently, the PROMETHEE method is harnessed to effectuate the ranking of 20 cryptocurrencies predicated on the identified criteria. Furthermore, the integration of LSTM enables the prediction of values for four predictable criteria, seamlessly incorporated into the PROMETHEE model to furnish rankings across diverse temporal intervals. The proposed model, thus, presents a holistic and pragmatic approach to inform investment decision-making within the dynamic cryptocurrency market. By embracing a comprehensive set of criteria and integrating predictive analytics, this model stands as a valuable contribution to the field, offering nuanced insights to stakeholders navigating the complexities of cryptocurrency investment.

In today’s competitive environment, multi-branch companies allocate their stores with the aim of expanding their territorial coverage to attract new customers and increase their market share. Consumer satisfaction surveys either produce global performance results or they are not able to differentiate consumer perceptions using location analytics. This research develops a novel framework to assist multi-branch companies in mapping the consumer satisfaction performance of their stores, expanding conventional customer relationship management to the spatial context. The framework developed proposes a decision model that combines the Group Decision Support extension of the PROMETHEE and CRITIC methods in a GIS environment to generate satisfaction performance mappings. The developed decision-making framework converts consumer responses into satisfaction performance maps, allowing the company’s stores and their competitors to be evaluated. Moreover, it provides insight into the potential opportunities and threats for each store. The performance of the proposed framework is highlighted through a case study involving a multi-branch coffeehouse company in a Greek city. Finally, a tool developed to assist the computational part of the framework is presented.

The most common situation encountered in the operating room scheduling is the uncertainty of operation times. This situation may cause the operations to be delayed or canceled. In this study, stochastic operating room scheduling is discussed under the uncertainty of operation times. In real life, variability may vary depending on many factors from operation to operation/patient to patient. These factors are the surgeon's experience, the difficulty of the operation, the patient's weight, age, disease history, etc. In this study, separate coefficients of variability were determined for each operation, taking into account the variability factors. Operations are scheduled, taking into account the operation-specific coefficients of variation. To evaluate the variability factors, analytical network process method was used considering the interaction between them. The level of uncertainty/coefficient of variation of each operation was determined with the PROMETHEE method. Finally, the logical modeling power of constraint programming is used to solve the operating room scheduling problem. In the proposed constraint programming model, the flexibility of the goal programming method was utilized. For the modeling of uncertainties, a chance-constrained approach was used. The case study demonstrates that the proposed approach is a novel and outstanding technique, and the proposed CP model is efficient in solving the problem. As a result of the study, the uncertainty in the operation time of each patient was calculated as the variability according to the factor weights, and the tables were reconstructed according to this situation. The performance and effectiveness of the new schedules obtained under variability are shown. [ABSTRACT FROM AUTHOR]

In the current research work, AA7050 a marine aluminium alloy was reinforced with the nano graphite particles processed through stir casting technique. The scanning electron microstructure reveals that the nano particles were uniformly distributed over the matrix material and the hardness of the composites increase with raise in weight percentage of Gr particles owing to the Hall-Petch effect. The wear experiments were conducted by varying reinforcement, load, velocity, distance and temperature. The experimental runs were designed using the L25 orthogonal array in which wear, coefficient of friction and worn surface hardness were recorded as response. The wear resistance of the composites increases with raise in the graphite content attributed to the formation of mechanical mixed layer, the wear rate transfer from mild to severe when there swift in temperature from 100 °C to 150 °C. The worn surface hardness of the composites was higher than the as cast composites owing to the presence of Fe on the surface confirmed through the EDAX mapping. The composites were optimized using the modified PROMETHEE optimization technique and results revealed that AA7050 reinforced with 8% Gr particles showed best result and recommended for the marine sector. [ABSTRACT FROM AUTHOR]

Failure modes and effects analysis (FMEA) is a systematic framework applied to recognize and eliminate viable failures within objects, services, structures, or designs at the early stage of the production process. The existing traditional FMEA approaches come with inherent deficiencies, e.g., all risk factors having similar weights, inappropriate and crisp risk priority numbers, and neglecting the existence of uncertainty and vagueness in experts' judgment. Our purpose is to identify the drawbacks of the existing models and then improve the risk assessment of failure modes under uncertain environments. For this purpose, we present a novel FMEA technique based on rough numbers and preference ranking organization method for enrichment evaluations (PROMETHEE) in multi-criteria decision-making problems. The presented FMEA model integrates the advantages of the PROMETHEE approach and the modified entropy weight method in coping with the roughness of linguistic assessment information. To illustrate its potential applications, the proposed method is tested to examine the risks of the general anesthesia process in the medical field. In the end, a comparison with the existing techniques is given to show the efficiency and accuracy of the proposed model. [ABSTRACT FROM AUTHOR]

Decision making process comprises complexity due to holistically managed requirements. Since this process has diverse effects on stakeholders as decision makers, undoubtedly, the decisions become more significant for organizations having critical decisions in today's globalized sustainable world. If these decisions influence not only providing human well‐being but also improving the quality of working life through measuring the performance of business processes, their results should be monitored more systematically. Through this viewpoint, in this paper, the applicability of ergonomics indicators, as the fundamental part of a systematic approach integrating ergonomics and sustainability to monitor and evaluate processes of organizations, is queried within a hybrid multi‐criteria perspective, including five evaluation criteria consolidated for this paper, through a designed survey by asking practitioners as potential users of such an approach. The used methods, that is, BWM and PROMETHEE, enable presenting a base study to decide which ergonomics indicators are necessary for developing a systematic approach, indicating the prioritization of these indicators to be used as candidates for the approach. Results show that 15 ergonomics indicators can be candidates for facilitating sustainable process performance measurement in ergonomics. Importantly, this paper proposes guidance in making decisions for achieving well‐managed processes in organizations through ergonomics indicators evaluated on a hybrid multi‐criteria perspective. [ABSTRACT FROM AUTHOR]

BACKGROUND: The high organic load and low biodegradability of the effluent from baker's yeast production limit its use as a substrate in microbial fuel cell (MFC) systems. In this study, baker's yeast production wastewater was used as a substrate in the anode chamber to assess the impact of various pretreatment methods [dilution, microwave (MW), acidic‐thermal, basic‐thermal and ultrasound (US)] on electricity generation and waste treatment. Additionally, azo dye was used as an electron acceptor at the cathode. Power density and coulomb efficiency were evaluated for electricity generation, and chemical oxygen demand (COD) removal and azo dye removal parameters were evaluated for treatability. RESULTS: The maximum power densities obtained were 83.53, 46.54, 19.41, 67.40, 41 and 33 mW m−2 for MW, acidic thermal, alkaline‐thermal and US pretreatments, diluted raw and raw wastewater, respectively. To determine the most suitable pretreatment method, PROMETHEE was performed using the criteria of maximum power density, COD removal, azo dye removal, coulombic efficiency and pretreatment cost. The most suitable method was found to be MW pretreatment. The order of the alternatives was found to be MW > US > acidic/thermal > diluted raw > raw > alkaline/thermal. With the MW pretreatment, 81.34% azo dye removal, 5 g L−1 COD removal, 0.27% coulombic efficiency and €0.284 L−1 pretreatment cost were obtained. CONCLUSION: The most suitable pretreatment method to be applied to wastewater for the treatment of baker's yeast production wastewater and high energy production was determined as MW using the PROMETHEE approach. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]