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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]

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.

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]

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.)

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]

Küreselleşme ve teknolojinin gelişmesi ile birlikte, gerek yurtiçi gerekse ithalat ve ihracatla artan ticari faaliyetler, bankaları ve bankacılık sektörünü de ekonomi açısından önemli bir noktaya getirmiştir. Bankaların finansal performans incelemeleri genellikle hem teorik hem de uygulama açısından önemli konuların başında gelmiştir. Literatürde birçok çok kriterli karar verme yöntemlerinin finansal performans ölçümleri amacıyla kullanıldığı görülmektedir. Bu çalışmada Türkiye’de faaliyet gösteren kamu, özel veya yabancı sermayeli 20 bankanın finansal performanslarının BWM tabanlı TOPSIS, PROMETHEE ve COPRAS yöntemleri ile ölçülmesi ve elde edilen bulguların karşılaştırmalı olarak yorumlanması amaçlanmıştır. Çalışmada bankalar CAMELS değişkenleri altında 10 kriter belirlenerek değerlendirilmiştir. Aynı zamanda çalışma sonucunda elde edilen bankaların sıralamasına ait sonuçlar Spearman sıra korelasyon analizi ile karşılaştırılmıştır. Çalışma 2009 ile 2020 yılları arasını kapsamaktadır. Çalışmanın sonucunda ise kamu bankalarının performans olarak daha yüksek olduğu ve yöntemler açısından her üç yöntem bulgularının benzer olduğu ancak uygulama kolaylığı ve sağladığı faydalı bilgiler açısından PROMETHEE yönteminin daha uygulanabilir olduğu sonuçlarına ulaşılmıştır. Bu sonuçların çok kriterli karar verme yöntemleri literatürüne ve bankacılık sektörüne katkı sağlayacağı düşünülmektedir.

Along with globalization and the development of technology, commercial activities that are increasing both domestically and with imports and exports have brought banks and the banking sector to an important point in terms of economy. Banks' financial performance researches are generally one of the most important issues in terms of both theory and practice. In the literature, it is seen that many multi-criteria decision making methods are used for financial performance measurements. In the study, it is aimed to measure the financial performances of 20 public, private or foreign capital banks operating in Turkey with BWMbased TOPSIS, PROMETHEE and COPRAS methods and to interpret the findings comparatively. In the study, banks are evaluated by determining 10 criteria under the CAMELS variables. At the same time, the results of the ranking of the banks obtained as a result of the study are compared with the Spearman rank correlation analysis. The study involves the years between 2009 and 2020. As a result of the study, it is concluded that public banks have higher performance and the findings of all three methods are similar in terms of methods, but the PROMETHEE method is more applicable in terms of ease of application and useful information it provides. It is thought that these results would contribute to the literature of multi-criteria decision making methods and the banking sector. [ABSTRACT FROM AUTHOR]

Copyright of Konya Journal of Engineering Sciences / Konya Mühendislik Bilimleri Dergisi is the property of Selcuk University Journal of Engineering, Science & Technology 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.)

Copyright of Rudarsko-Geolosko-Naftni Zbornik is the property of Faculty of Mining, Geology & Petroleum Engineering 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.)

Indoor Environmental Quality (IEQ) has received a great deal of attention in recent years due to the relationship between worker comfort and productivity. Many academics have studied IEQ from both a building design and an IEQ assessment perspective. This latter line of research has mostly used direct eliciting to obtain weights assigned to IEQ categories such as thermal comfort, visual comfort, acoustic comfort, and indoor air quality. We found only one application of indirect eliciting in the literature. Such indirect eliciting operates without the need for imprecise direct weighing and requires only comfort evaluations, which is in line with the Industry 5.0 paradigm of individual, dynamic, and integrated IEQ evaluation. In this paper, we use a case study to compare the only indirect eliciting model already applied to IEQ, based on TOPSIS, to an indirect eliciting method based on PROMETHEE and to a classical direct eliciting method (AHP). The results demonstrate the superiority of indirect eliciting in reconstructing individual preferences related to perceived global comfort. [ABSTRACT FROM AUTHOR]

In this study, a framework to circumvent the difficulties in selecting a proper flood routing method was established by employing two different multi-criteria decision analysis (MCDA) tools, namely, TOPSIS and PROMETHEE, with definite decisive criteria such as the error metrics, the number of model parameters, and the model background, under three scenarios. For eight distinct flood datasets, the parameters of 10 different Muskingum models were determined using the water cycle optimization algorithm (WCOA) and the performance of each model was ranked by both MCDA tools considering the hydrograph types of flood datasets, labeled as smooth single peak, non-smooth single peak, multi-peak, and irregular. The results indicate that both tools were compatible by giving similar model results in the rankings of almost all scenarios that include different weights in the criteria. The ranking results from both tools also showed that the routing application in single-peak hydrographs was examined better with empirical models that have a high number of parameters; however, complex hydrographs that have more than one peak with irregular limps can be assessed better using the physical-based routing model that has fewer parameters. The proposed approach serves as an extensive analysis in finding a good agreement between measured and routed hydrographs for flood modelers about the estimation capabilities of commonly used Muskingum models considering the importance of correlation, model complexity, and hydrograph characteristics. [ABSTRACT FROM AUTHOR]

Copyright of Economics & Environment / Ekonomia i Środowisko is the property of Fundacja Ekonomistow Srodowiska i Zasobow Naturalnych 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.)

The selection of mining methods is a challenging and complicated concept in mining engineering. It depends on various and different factors such as geotechnical, geological and economic properties and characteristics. Kodakan Gold Mine in Iran is currently mined using the open pit method. However, due to the special conditions of this mine and the increase in waste removal costs, it is inevitable to decide to select an underground mining method in the future. The purpose of this research is to select the most proper underground mining method for this mine. The shape, dip, and depth of the deposit, the thickness of the ore, grade distribution, recovery, skilled manpower, output per worker, and strength specifications of the ore, hanging-wall, and footwall are considered as the main decision attributes. Since there are different parameters in selecting the appropriate mining method using the multi-attribute decision making approach, therefore hybrid multi-attribute decision-making method was employed in this paper to enhance the strength of the decision model and eliminate the weaknesses of the classical methods. Regarding the results of this study, rock quality designation of the hanging-wall and deposit shape have the highest weight value in selecting the underground mining method. Moreover, the shrinkage mining method is proposed as the most appropriate method.

Various decontamination technologies have been developed for removing contaminated areas in industries. Although it is important to consider parameters such as safety, cost, and time when selecting the decontamination technology, till date their comparative study is missing. Furthermore, different decontamination technologies influence the decontamination effects in different ways. Therefore, this study compares different decontamination techniques for the steam generator using a multicriteria decision-making method. A steam generator is a large device comprising both low- and very low-level waste (LLW, VLLW) and reflects the difference in weights of the standards according to the classification of the waste. For LLW and VLLW decontaminations, chemical oxidizing reduction decontamination (CORD) and decontamination grit blasting were used as the preferred techniques, respectively, considering the purpose of decontamination differs based on the initial state of waste. An expert survey revealed that safety in LLW and waste minimization in VLLW exhibited high preference. This evaluation method can be applied not only to the comparison between each process, but also to the creation of process scenarios. Therefore, determining the decontamination approach using logical decision-making methods may improve the safety and economic feasibility of each step in the decommissioning process and ensure a public acceptance.

Background: Network meta-analysis exploits randomized data to compare multiple interventions and generate rankings. Selecting an optimal treatment may be complicated when multiple conflicting outcomes are evaluated in parallel. Design: The present study suggested the incorporation of multicriteria decision-making methods in network meta-analyses to select the best intervention when multiple outcomes are of interest by creating partial and absolute rankings with the TOPSIS, VIKOR, and PROMETHEE algorithms. The TOPSIS and VIKOR techniques represent distance-based methods for compromise intervention selection, whereas the PROMETHEE analysis method allows the definition of preference and indifference thresholds. In addition, the PROMETHEE technique allows a variety of modeling options by selecting alternative preference functions. Different weights may be applied to outcomes objectively with the entropy method as well as subjectively with the analytic hierarchy process, enabling the individualization of treatment choice depending on the clinical scenario. Results: Visualization of decision analysis may be performed with multicriteria score-adjusted scatterplots, while league tables may be constructed to depict the PROMETHEE I partial ordering of interventions. A simulated study was performed assuming equal weights of outcomes, and the TOPSIS, VIKOR, and PROMETHEE II methods were compared using a similarity coefficient, indicating a high degree of agreement among methods, especially with higher numbers of interventions. Conclusions: Multicriteria decision analysis provides a flexible and computationally direct way of selecting compromise interventions and visualizing treatment selection in network meta-analyses. Further research should provide empirical data about the implementation of multicriteria decision analysis in real-world network meta-analyses aiming to define the most suitable method depending on the clinical question. Highlights: Multicriteria decision-making methods can be implemented in network meta-analysis to indicate compromise interventions. The TOPSIS, VIKOR, and PROMETHEE methods can be used for optimal treatment selection when conflicting outcomes are evaluated. The weights of outcomes can be defined objectively or subjectively, reflecting the priorities of the decision maker. Graphical Abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

Decision makers increasingly operate in real-time information-rich environments, where limited time is available for interpreting data to inform decisions. These environments are driven by static or mobile sensing devices that can provide numerous dynamic data points. A prominent approach in this space is to utilise drones, which can be deployed to gather targeted information. However, deciding how best to deploy available drones is nontrivial, and stands to benefit from decision support aids that plan routes. Such a system must operate under time constraints created by the changing attributes of routes as the situation unfolds. This study describes a dynamic decision support system (DSS) for situational awareness with drones. The system applies Multi-Criteria Decision Making (MCDM) methods within a dynamic genetic algorithm to provide a continuously revised ranking of routes. Five desiderata for dynamic decision support are presented. It is shown how a dynamic DSS can be equipped with declarative specification of preferences (Desiderata 1), dynamic revision of recommendations (Desiderata 2), and high diversity of options (Desiderata 3). The study then compares four MCDM methods, namely the Weighted Product Model (WPM), the Analytic Hierarchy Process (AHP), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and the Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), with regards to how consistently they trade-off between criteria (Desiderata 4) and the stability of results under small changes to criteria values (Desiderata 5). To evaluate the trade-offs between criteria we analyse the smoothness of change in criteria outcomes as criteria weightings increase for each algorithm. The outcomes are calculated by automating the selection of routes in a case study that applies drones to the task of harbour management. The stability of results for the different MCDM methods are compared. Perturbations were applied to sets of routes ranked by each algorithm then each algorithm was reapplied and the magnitude of the changes in ranking was assessed. Overall, TOPSIS was found to be the algorithm which made the most consistent trade-offs between criteria, only under-performing another algorithm with respect to a single criterion. AHP and WPM were the next most consistent algorithms and PROMETHEE was the least consistent algorithm. TOPSIS was also found to be the most stable method under small changes to criteria values. AHP was the second most stable, followed by PROMETHEE and WPM respectively. The results show that TOPSIS achieves the best result for both Desiderata 4 and 5 and consequently the study finds TOPSIS to be an appropriate MCDM method for dynamic decision support. • Desired features for dynamic decision support systems are introduced. • A dynamic decision support system for situational awareness with drones is outlined. • TOPSIS identified as most suitable MCDM method for dynamic decision support. [ABSTRACT FROM AUTHOR]

The present study aims to create groups of symmetrical autonomous metro lines that are united by common features. An integrated six-step methodology which proposes a new aggregated approach for multi-criteria evaluation of fully autonomous metro systems was proposed. The first step determines the criteria to assess the autonomous metro system. Eight criteria connected to the safety, infrastructural and technological development of the autonomous metro system were chosen. In the second step, 20 fully autonomous metro systems in European countries were selected as alternatives. The determination of the criteria weights was performed in the third step based on objective, subjective and combined approaches. For this purpose, the Shannon Entropy method and BWM (Best Worst method) were applied. The fourth step presents the ranking of the autonomous metro system by using multi-criteria methods. Three approaches were studied: distance-based, utility-based and outranking approaches. The distance-based approach includes the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and EDAS (Evaluation Based on Distance from Average Solution) methods; the utility-based approach includes MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and COPRAS (COmplex PRoportional Assessment) methods; the outranking approach includes the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) method. The final ranking based on the new aggregative approach was carried out in the fifth step. Thus, Laplace's criterion was applied to the final ranking. The Hurwitz's criterion was used to verify the results. In the sixth step, the verification of the results was performed by applying cluster analysis. In was found that Line 1 in Paris is the best. Line 14 in Paris and Line D in Lyon were ranking in the second and third position, respectively. The autonomous metro in Brescia, Line C in Rome, and Line M2 in Lausanne were placed at the end of the ranking. Finally, four clearly formed groups of autonomous metro were proposed. The novelty of this study and its main advantage entails the elaboration of a new aggregated approach of multi-criteria methods, evaluation of the autonomous metro systems' performance and determination for the groups of symmetrical autonomous lines in European countries. [ABSTRACT FROM AUTHOR]

Indoor Environmental Quality (IEQ) has received a great deal of attention in recent years due to the relationship between worker comfort and productivity. Many academics have studied IEQ from both a building design and an IEQ assessment perspective. This latter line of research has mostly used direct eliciting to obtain weights assigned to IEQ categories such as thermal comfort, visual comfort, acoustic comfort, and indoor air quality. We found only one application of indirect eliciting in the literature. Such indirect eliciting operates without the need for imprecise direct weighing and requires only comfort evaluations, which is in line with the Industry 5.0 paradigm of individual, dynamic, and integrated IEQ evaluation. In this paper, we use a case study to compare the only indirect eliciting model already applied to IEQ, based on TOPSIS, to an indirect eliciting method based on PROMETHEE and to a classical direct eliciting method (AHP). The results demonstrate the superiority of indirect eliciting in reconstructing individual preferences related to perceived global comfort.

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic 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.)

Today, the use of renewable energy sources is increasing day by day. The essential advantages of wind energy are that it is clean, low cost, and unlimited. In this paper, the wind energy potential of provinces of the Marmara region in Turkey was evaluated by multi-criteria decision-making (MCDM) methods. In the study, TOPSIS and PROMETHEE methods were used for analysis criteria weights were determined by two different approaches. In the first approach, the criteria weights were taken equally. In the second approach, the criteria were weighted using the AHP method. When the methods were applied by taking the criteria weights equally, Balıkesir and Çanakkale were determined as wind priority provinces in potential, while Kocaeli and Sakarya took the last rank. After the criteria weights were determined via AHP when TOPSIS and PROMETHEE methods were applied, Balıkesir ranked first, and Kocaeli ranked last. Spearman's Correlation Coefficient determined the level and direction of the relationship between the rankings obtained from TOPSIS and the PROMETHEE method. When the methods were applied, the value of “0.636” indicated that the relationship between the rankings was “positive” and “moderate”. When the criteria were weighted with AHP and the methods were applied, the correlation coefficient was obtained as “0.909”. This value indicated a “positive” and “very high” level of relationship. It was determined that the ranking results obtained when the methods were applied after the criterion weights were calculated with AHP were more supportive of each other.

Copyright of Journal of Polytechnic is the property of Journal of Polytechnic 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.)

Multicriteria methods have gained traction in academia and industry practices for effective decision-making. This systematic review investigates and presents an overview of multi-criteria approaches research conducted over forty-four years. The Web of Science (WoS) and Scopus databases were searched for papers on multi-criteria methods with titles, abstracts, keywords, and articles from January 1977 to 29 April 2022. Using the R Bibliometrix tool, the bibliographic data was evaluated. According to this bibliometric analysis, in 131 countries over the past forty-four years, 33,201 authors have written 23,494 documents on multi-criteria methods. This area's scientific output increases by 14.18 percent every year. China has the highest percentage of publications at 18.50 percent, followed by India at 10.62 percent and Iran at 7.75 percent. Islamic Azad University has the most publications with 504, followed by Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. Expert Systems with Applications, Sustainability, and the Journal of Cleaner Production are the top journals, accounting for over 4.67 percent of all indexed works. In addition, E. Zavadskas and J. Wang have the most papers in the multi-criteria approaches sector. AHP, followed by TOPSIS, VIKOR, PROMETHEE, and ANP, is the most popular multi-criteria decision-making method among the ten nations with the most publications in this field. The bibliometric literature review method enables researchers to investigate the multi-criteria research area in greater depth than the conventional literature review method. It allows a vast dataset of bibliographic records to be statistically and systematically evaluated, producing insightful insights. This bibliometric study is helpful because it provides an overview of the issue of multi-criteria techniques from the past forty-four years, allowing other academics to use this research as a starting point for their studies. [ABSTRACT FROM AUTHOR]

The sustainability of energy systems is increasingly assessed for development of more resilient, greener district heating (DH) systems. That requires compiling technological, environmental, and economic indicators in a social, political, and institutional context. This work investigates DH system sustainability analysis by five frequently applied multi-criteria decision analysis (MCDA) methods—WSM, TOPSIS, PROMETHEE, ELECTRE and DEA. To compare the sustainability assessment results, a selection of 8 criteria describing 12 DH companies (DHC) was examined. Sensitivity analysis was performed to determine the most credible MCDA method. Criteria weights were changed: (1) individually for evaluation of the range of stability for alternatives (score of DHC performance); (2) individually by a fixed value to compare how each criterion weight change affected the average score of a result; and (3) to compare the AHP weighting method to an equal weight scenario. The results of sensitivity analysis along with literature investigation shows that all methods are suitable for sustainability analyses of DH systems while also having differences in the calculation process and in the interpretation of results. The generalized algorithm for sustainability analysis in the energy sector outlined in this study along with the documented features of the main MCDA methods can be used as a guide for future assessment of energy systems by researchers and industry professionals. [ABSTRACT FROM AUTHOR]

Drilling is the first stage of open pit mining that has a considerable effect on the other stages of mining, including blasting, loading, hauling and crushing. An unsuitable drilling pattern may lead to undesirable results such as poor fragmentation, back break and fly rock that not only results in technical and safety issues but also increases the operating cost of the mine. Multi-Attribute Decision-Making (MADM) methods can be useful approaches to select the appropriate drilling pattern among various alternatives, performed previously. This paper aims to select the most proper drilling and blasting pattern for Sangan Iron Mine, Iran. To achieve this, in the first step, rock fragmentation, back break, fly rock, specific charge and specific drilling were considered as the decision criteria and their degree of importance was calculated using the AHP method under a fuzzy environment. Then, TOPSIS and PROMETHEE methods were used to select the most proper alternative. The results of this study show that the drilling pattern with a spacing of 5 m, burden 4 m, hole depth 10 m, and hole diameter 15 cm is the most suitable one. The stemming length and powder factor of the suggested pattern are 2.3 m and 2.6 gr/cm3, respectively.

Mechanical ventilator (MV) is used to help the patient breathe by delivering gas to the lungs at a certain rate using positive pressure. The complex evaluation of mechanical ventilator devices at present time is a very important and topical issue, due to the presence of many mechanical ventilator companies, as it seems that the process of evaluation and selection of ventilator equipment needs strong experience in this field. Our paper show that multi criteria decision making (MCDM) methods can be applied to comparing and evaluating some alternatives of mechanical ventilator devices. This study will determine new methodology to help the decision makers to choosing the best mechanical ventilator among the five alternatives based on eight criteria; Cost of the MVdevice; Maximum Inspiratory flow;Maximum Pressure; Tidal volume; PEEP;Weight of ventilator; Screen size and Internal battery time. This study used two techniques; TOPSIS technique and PROMETHEE II technique. Our paper used the same weights criteria in these two techniques. The weight for each criteria should be determined by the medical engineer expert and the decision makers. Choosing mechanical ventilator will affect the quality of the therapeutic and diagnostic processes, the way the treating doctor works, and also affect the patient's comfort. Because of these reasons, we designed a new methodology based on MCDM. The aim of this research is to design a new method for evaluating ventilator machines and medical technology for the purpose of purchasing ventilator devices in hospitals. The choice of the appropriate ventilator device is a big problem among the decision-makers so that its purchase must be transparent. The new method will serve as the basis for making the decision in purchasing a ventilator. This research dealing with effective procurement will become part of the entire decision-making chain as the expected usability of the device also must be considered. [ABSTRACT FROM AUTHOR]

The organization Performance management is an important component that directly affects the total performance of the organization and the competitive environment. Hence, manager(s) performance is one of the most important functional parts of an organization. Senior manager(s) decisions are one of the most important factors affecting the organization performance management. In this paper, organization performance management is evaluated using criteria derived from Balanced Scorecard. The purpose of this paper is to prioritize alternatives related to manager(s) performance in an organization using multi-criteria decision-making, i.e. PROMETHEE, ELECTRE, and TOPSIS and provide a model for it. Mean Maximum-Minimum Square Ranks method is proposed to combining the results obtained from applying multi-criteria decision-making methods. Also, roadmaps are presented for alternatives with higher priority for the organization. The proposed model provides the possibility of solving issues related to the organizational performance by analyzing various alternatives and criteria for organization manager(s). To evaluate the efficiency of the proposed approach, the model is implemented in a petrochemical company, which its final products are used to make fibers.

The present study aims to create groups of symmetrical autonomous metro lines that are united by common features. An integrated six-step methodology which proposes a new aggregated approach for multi-criteria evaluation of fully autonomous metro systems was proposed. The first step determines the criteria to assess the autonomous metro system. Eight criteria connected to the safety, infrastructural and technological development of the autonomous metro system were chosen. In the second step, 20 fully autonomous metro systems in European countries were selected as alternatives. The determination of the criteria weights was performed in the third step based on objective, subjective and combined approaches. For this purpose, the Shannon Entropy method and BWM (Best Worst method) were applied. The fourth step presents the ranking of the autonomous metro system by using multi-criteria methods. Three approaches were studied: distance-based, utility-based and outranking approaches. The distance-based approach includes the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and EDAS (Evaluation Based on Distance from Average Solution) methods; the utility-based approach includes MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and COPRAS (COmplex PRoportional Assessment) methods; the outranking approach includes the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) method. The final ranking based on the new aggregative approach was carried out in the fifth step. Thus, Laplace’s criterion was applied to the final ranking. The Hurwitz’s criterion was used to verify the results. In the sixth step, the verification of the results was performed by applying cluster analysis. In was found that Line 1 in Paris is the best. Line 14 in Paris and Line D in Lyon were ranking in the second and third position, respectively. The autonomous metro in Brescia, Line C in Rome, and Line M2 in Lausanne were placed at the end of the ranking. Finally, four clearly formed groups of autonomous metro were proposed. The novelty of this study and its main advantage entails the elaboration of a new aggregated approach of multi-criteria methods, evaluation of the autonomous metro systems’ performance and determination for the groups of symmetrical autonomous lines in European countries.

Agriculture is a crucial and strategic sector for developing countries. The agricultural sector in Turkey has been suffering from regression in recent years due to several reasons. In an attempt to reverse this process, we analyze the cultivation possibilities of high profit-margin crops in Turkish lands and develop a ranking among eight alternative crops. To perform a comprehensive analysis encompassing several dimensions, three MCDM methods are utilized; namely fuzzy AHP to determine the weights of evaluation criteria, and TOPSIS and PROMETHEE to develop a ranking among the crop alternatives. The crop alternatives are evaluated against several economic, technical, social and environmental criteria. The results favor the cultivation of soy bean, goji berry and buckwheat, while tamarind appears to be the least favored crop among the considered alternatives. The analysis results are enhanced with a sensitivity analysis. [ABSTRACT FROM AUTHOR]

The main goal of power plants is to generate the electricity in sustainability perspective consisting of the principles of environmental awareness, reliability, efficiency, economy and uninterruptedness. Complying with the operational directives and maintenance are twin pillars for achieving this comprehensive goal. Within this scope, this study handles the maintenance strategy selection problem which is the first step of the effective maintenance management for one of the most important equipment groups among thousands of equipment in one of the large-scale hydroelectric power plants which have great importance for Turkey energy mix with approximately a fifth share in the total generation. So as to determine the most critical equipment group AHP-TOPSIS combination is used. For the selected equipment group, the most appropriate of all applicable 4 maintenance strategies are determined via PROMETHEE, which has been limited used for the maintenance strategy selection problem in the literature despite its advantages. As a result of this study which is the first in the literature with its method configuration and its application in hydroelectric power plants, a 1-year observation is conducted to confirm the proposed approach, and a 100% improvement is achieved in the unit shutdowns resulting from the selected equipment. [ABSTRACT FROM AUTHOR]

This paper develops a multi-objective conflict resolution simulation-optimization model based on a leader-follower game to resolve conflicts between different water users while optimizing water quality in the river through selective depth water withdrawal from the reservoir. Iran Water Resources Management Company (IWRMC), given the nature of the power distribution in this region, is selected as leader, and agricultural, domestic, and industrial water users are selected as followers. Nash-Harsanyi bargaining theory is used as a nested model in this general framework to model competition between followers. The proposed selective withdrawal approach considers four reservoir outlets, located at 120, 145, 163, and 181 m above sea level. Water withdrawal from multiple outlets addresses reservoir thermal stratification and water quality. Temperature and water quality are simulated based on different possible scenarios of reservoir inflow and release using a calibrated CE-QUAL-W2 model. Five artificial neural network (ANN) surrogate/meta models are then trained and validated based on CE-QUAL-W2 model results for each water quality variable. Subsequently, these validated surrogate models are coupled with the NSGA-II optimization model, which along with the utility functions of different stakeholders, constitute the building blocks of our conflict resolution multi-objective optimization model. Finally, three decision-making methods, namely AHP, PROMETHEE, and TOPSIS, are utilized to choose the superior compromise solution. Our results show that water withdrawal from multiple reservoir outlets ensures optimal water allocation to different stakeholders while satisfying the desired water quality criteria. In this study, the top outlet (181 m) has desirable quality, and the IRWQISC water quality criterion at the top and deepest outlets are highest and lowest, respectively. [ABSTRACT FROM AUTHOR]

Goal: This paper analyses how European countries of Global Innovation Indicators (GII) present in the ranking by multicriteria support aid analysis. Design / Methodology / Approach: The methodology uses Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking countries and PROMETHÉE (Preference Ranking Organisation Method for Enrichment Evaluations) for outranking them. Results: There was change in 30 ordered positions from 39 countries observed. At non-compensatory method the overrating become “easier” than the compensatory method, especially when there are many alternatives and criteria for computing with small difference among values. Limitations of the investigation: It is only used the GII 2015 Europe for continuing investigations about MCDA realized for Latin America (2017) and Asia and Africa (2019). Practical implications: The applications result in a different understanding about TOPSIS ranking application, from original score list at GII; and also the perception of organized groups at outranking application. Originality / Value: Observing GII via MCDA is possible to see changing’s in the ranking according to countries profiles different from GII raking. Although European profiles seem to be similar, it is important to observe other perspective of grouping by them; suggesting quantitative studies inclusion and innovative trends.

The aim of this paper is to develop a simulation-aided PROMETHEE-TOPSIS approach for the selection of the most desirable groundwater remediation strategies. The combination methods enables a careful evaluation of the identified remediation alternatives in which their strong and weak points can be detected and a ranking is provided which facilitates the final selection for the decision-maker. The capabilities and effectiveness of the developed method are illustrated through a case study on the remedial alternative selection for a naphthalene contaminated site in Anhui, China. Four attributes (i.e., total pumping rate, total cost, mean residual contaminant concentration and maximum excess life time cancer risk) for fifty remedial alternatives in each duration are considered and analytic hierarchy process is used to determine the weight of attributes importance. The results demonstrates that the developed method could help decision makers obtain the useful ranking information strategies that covering a variety of decision-relevant remediation options, which is beneficial for public health and environmental protection. [ABSTRACT FROM AUTHOR]

The premier regulatory bodies for technical education in India have mandated several services and facilities for the students of technical institutes. These services and facilities not only help in improving the learning environment in an educational institute but also boost the morale of students thereby enhancing the brand image of the institute. In India, the private un-aided technical institutes do not receive any direct financial support from the government for their day to day working. Considering the limited resources at their disposal, the management of the un-aided technical educational institutes may find it difficult to upgrade all services and facilities simultaneously. It is therefore necessary to shortlist services and facilities that need immediate attention and determine the proportion in which the available budget should be utilized for these services and facilities. A two stage survey was designed and opinion of 1090 students was collected through Google Form. Out of the 14 services and facilities extended by the institute, 4 were shortlisted with the help of first survey. Data collected through second survey was used as a basis for determining the values of attributes. TOPSIS method was then employed to prioritize the shortlisted services and facilities. Finally fund allocation was calculated for every attribute. Results indicate that in the opinion of the students, quality of the mess is the most significant issue and necessitate maximum fund allocation. Parking appears to be the least significant issue and hence minimum funds can be allotted for this aspect. The analysis is based on the facilities extended by the institute and opinion of the students. A similar exercise can be extended to any educational institution or organization wi th suitable modifications. The study is unique and serves as a guideline to the management of private un-aided technical institutions in fund allocation. This study is an attempt to present a novel approach for improving quality of learning environment in un-aided technical institutes. [ABSTRACT FROM AUTHOR]

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In this study, a model based on multi criteria decision making methods is established to analyze the financial performance of 11 Turkish banks with public, private and foreign capital. The aim of this study is to make a comparison of TOPSIS and PROMETHEE methods which are used in evaluation of bank performance. In this model, where 13 financial ratios are used as criteria, banks are ranked from the highest performance to the lowest. The rankings are compared with each other and with the most basic performance criteria, namely the return on assets and the return on equity. According to the comparative analysis, both PROMETHEE and TOPSIS methods are effective evaluation tools in determining the bank performance. [ABSTRACT FROM AUTHOR]