Complex Proportional Assessment Research Articles

New complex proportional assessment approach using Einstein aggregation operators and improved score function for interval-valued Fermatean fuzzy sets

As a generalization of the Fermatean fuzzy set, the theory of interval-valued Fermatean fuzzy set (IVFFS) is a more robust and reliable tool to address the imprecise and incomplete information in the process of multi-criteria decision making (MCDM), thus can be employed on wider range of applications. The aim of this study is to purpose a novel decision-making approach by combining two well-recognized methods, named as the criteria interaction through inter-criteria correlation (CRITIC) and the complex proportional assessment (COPRAS) with IVFFSs. In this line, to compare the interval-valued Fermatean fuzzy numbers (IVFFNs), a new score function is proposed and its feasibility in comparison with existing interval-valued Fermatean fuzzy score and accuracy functions is discussed. To combine the various IVFFNs, some interval-valued Fermatean fuzzy Einstein aggregation operators are introduced. Further, the CRITIC is utilized to derive the objective weights of attributes within IVFFS context. To prioritize the alternatives, the IVFF-COPRAS method is presented on IVFFSs settings. Later, to assess the performance quality of the developed methodology, an illustrative case study is discussed to evaluate and rank the sustainable community-based tourism (CBT) location candidates. Moreover, the comparative study and sensitivity investigation are conducted to prove that the developed framework efficiently handles the problem of sustainable CBT locations evaluation and selection problem under IVFFSs environment. The findings of this study conclude that the developed method is a systematic, more comprehensive, accurate, and structured approach in the assessment of sustainable CBT locations under uncertain environment.

Penentuan Kenaikan Jabatan Menggunakan Pembobotan Metode AHP dan Didukung Metode Complex Proportional Assessment

The internal state of the industry related to the human energy sources owned by the industry requires something that requires a management system that can support the selection of competent human energy sources in their field. The increase in problems is very meaningful for every industry because it involves the continuation of the growth of the industry. On the issue of promotion, managers must pay attention to many things about applicable problems, not subjective. Problems that often occur in the process of promotion of employees include the subjectivity of decision making, the presence of most employees who have far different abilities. Therefore we need a decision support system that can assist in determining effective position assignments and searching for the highest value using the COPRAS method. This decision support system uses the Analytical Hierarchy Process (AHP) method and (COPRAS) Complex Proportional Assessment where this method can be used to overcome complexity because there are many criteria that must be considered in promotions such as work quality, work experience, employee skills, tardiness, absenteeism. , teamwork, responsibility, and the final diploma. The data used is the assessment in 2020 at PT. Ark Setia has as many as 13 employee data. Testing the system was tried with one trial, namely making a start with Microsoft Office Excel. The results of the experiment using Microsoft Office Excel can be adjusted to the data that has been calculated using the AHP weighting method with the support of the COPRAS method, the highest value obtained from this calculation is 100.00 and obtained 4 appropriate results and fit to get the promotion.

Sustainable Supply Chain Risk in Food Packaging Industry: Integrated Delphi-CRITIC-COPRAS Method Using Fuzzy Set Theory

The present study aims to develop a framework for sustainable supply chain risk management evaluation in the food packaging industry based on multi-criteria decision-making (MCDM) methods in the fuzzy environment. An integrated MCDM approach is proposed based on Delphi, CRiteria Importance Through Intercriteria Correlation (CRITIC), and COmplex PRoportional ASsessment (COPRAS) methods. Through reviewing the research literature, related criteria were identified and selected based on experts' opinions and the fuzzy Delphi method. The fuzzy CRITIC method was used to determine the weights of the criteria. Finally, based on weighted indices and the fuzzy COPRAS method, food packaging suppliers were ranked according to their ability to manage the risks of sustainable supply chain activities. The results show that operational risks are essential in evaluating suppliers' risks in sustainable supply chain activities in the food packaging industry. Also, the three sub-criteria with the highest weights are defined as product quality risk, machines and equipment risks, and restrictions on green processes.

Selection of Cold Chain Logistics Service Providers Based on a Grey AHP and Grey COPRAS Framework: A Case Study in Vietnam

Choosing the most suitable cold chain logistics service providers (CLPs) is a vital strategic decision for businesses aiming to achieve an effective and sustainable cold supply chain. A sustainable CLP is one that integrates sustainable practices across its whole operation cycle to achieve product quality, on-time deliveries, and satisfied customer requirements, while preventing products from going to waste, which is especially important in the context of a developing country. This study aims to evaluate and select the best CLP regarding their sustainability performance. For this evaluation, a multi-criteria decision making (MCDM)-based framework is proposed that integrates the grey analytic hierarchy process (G-AHP) and grey complex proportional assessment (G-COPRAS) methodologies, in which grey numbers are used to express the linguistic evaluation statements of experts. Initially, the evaluation criteria based on service level, economic, environmental, and social dimensions were determined by means of a literature review and experts’ opinions to employ the MCDM approach. The G-AHP was utilized to identify the criteria weights, and then, G-COPRAS was used to select the best CLP among the alternatives. A case illustration in Vietnam is presented to exhibit the presented approach’s applicability. From the G-AHP findings, product quality, logistics costs, innovation, and effectiveness of cold chain processes, customer experience, and CO emissions of refrigerated vehicle were ranked as the five most important criteria. From the G-COPRAS analysis, Yoshida Saigon Cold Logistic (CPL-05) is the best CLP. The robustness of the applied integrated MCDM approach was also tested by conducting a comparative analysis, in which the priority rankings of the best CLPs were very similar. The assessment in this study is directed towards enabling managers, practitioners, and stakeholders of cold chain businesses to assess the most efficient CLP in the supply chain in the market and also to devise suitable strategies toward sustainable development.

The impact of social welfare and COVID-19 stringency on the perceived utility of food apps: A hybrid MCDM approach

The COVID-19 pandemic has created enormous challenges for society due to the various ways of impacting health. This paper focuses on the impact of the COVID-19 pandemic on people's food consumption patterns in the online environment. We investigate food app reviews and examine whether countries with a high rate of success with COVID-19 control consume more unhealthy food through mobile apps. We also investigate whether the population of countries with low social welfare eat more unhealthy food during the COVID-19 pandemic compared to countries with high social welfare. We take a hybrid multi-criteria decision making (MCDM) approach to calculate indexes based on the technique for order of preference by similarity to an ideal solution, complex proportional assessment, and VlseKriterijuska Optimizacija I Komoromisno Resenje. Results show that country social welfare and success in COVID-19 control negatively affect the perceived utility of the apps. Also, success in COVID-19 control and the perceived utility of food apps positively affect the proportion of unhealthy reviews, whereas social welfare has a negative impact. The results have important implications for public health policymakers, showing that the online food environment can be an important setting for interventions that seek to incentivize healthy eating.

Planning and establishment of battery swapping station - A support for faster electric vehicle adoption

Establishing Battery Swapping Station (BSS) is categorized as one of the means that can ignite faster adaptability of Electric Vehicles (EVs). For the lucrative performance of BSS, proper selection of an ideal location is crucial. This study uses the concept of the Fuzzy with Multiple Criteria Decision Making (MCDM) method to plan the optimum location of BSS, and is also an innovative type of work done on Indian subcontinent as per the knowledge of authors. With reference from some existing research and literature, an evaluation system is established, and then different criteria from economic, technical, and social aspects are considered for site selection of BSS. The TFN (Triangular Fuzzy Number) has been used to overcome the uncertainty due to insufficient information. Then, using Fuzzy based TFN Method with consideration of the preference within the criteria; weights of the criteria are obtained. Further COPRAS (Complex Proportional Assessment of Alternatives) methodology is applied to rank the selected locations in Kolkata Metropolitan Area (KMA), India. This paper concludes that the cost-related criteria like payback period, land acquisition cost, and machinery purchasing cost dominate other criteria. The area under Kolkata Municipal Corporation and the Western part of North 24 Parganas rank higher than other selected locations; thus, they are suitable for establishing BSS within the KMA, India. The outcome of this paper becomes vital for stakeholders and planners to select the optimum location of BSS. The approached methodology in this paper can be used in any analogous research with the related objective.

A single-valued neutrosophic decision framework for the assessment of sustainable transport investment projects based on discrimination measure

PurposeThe study aims at evaluating the most appropriate transport project which is one of the critical concerns of transport infrastructure scheduling. This process will be applied considering a set of criteria and discussed alternatives with sustainable perspectives.Design/methodology/approachIn this paper, a complex proportional assessment (COPRAS) framework is discussed to handle the sustainable transport investment project (STIP) assessment problem within a single-valued neutrosophic set (SVNSs). To form the procedure more useful in handling with uncertain features, a SVNS is applied as a valuable procedure to handle uncertainty. First, a new discrimination measure for SVNSs is introduced and discussed some elegant properties to determine the significance degree or weight values of criteria with the sustainabality perspectives. Second, an integrated approach is introduced based on the discrimination measure and the COPRAS method on SVNSs and named as SVN-COPRAS.FindingsA case study of an STIP evaluation problem is used to confirm the practicality and effectiveness of the SVN-COPRAS framework. Lastly, comparative discussion and sensitivity investigation are illustrated to prove the strength and solidity of the proposed framework.Originality/valueThe SVNSs enrich the essence of linguistic information when a decision expert (DE) vacillates among different linguistic values (LVs) to measure a sustainable transport project alternative problem. The utilization of SVNSs provides a more stable procedure to describe DEs' evaluations. So, an elegant methodology is developed to incorporate the DEs' awareness and experience for electing the desired STIPs. The introduced methodology has higher operability than the single-valued neutrosophic set technique for order preference by similarity to an ideal solution (SVN-TOPSIS) procedure during the larger numbers of attribute(s) or option(s). For the SVN-COPRAS methodology, there is no need to estimate the single-valued neutrosophic ideal solution (SVN-IS) and single-valued neutrosophic anti-ideal solution (SVNA-IS). The outcomes are calculated with handling the realistic data, which elucidates that the introduced model can tackle more intricate and realistic multi-criteria decision-making issues.

Towards sustainable cities: A sustainability assessment study for metropolitan cities in Turkey via a hybridized IT2F-AHP and COPRAS approach

Accelerating trends of urbanization enforce the integration of sustainability principles into urban planning in a local scale to foster prosperity for the next generation of cities. This study incorporates fifty-three indicators on economic, social, environmental, and institutional dimensions to develop a Sustainable Cities Index (SCI) and assess the sustainability performance of thirty metropolitans in Turkey over 2010-2018. Turkish metropolitans constitute an appealing case study due to the rapid urbanization within the same time span. To answer how new metropolitans have been doing and whether they perform better than formerly declared metropolitans in Turkey, we propose a novel methodology with three stages that hybridizes Interval Type-2 Fuzzy Analytical Hierarchy Process (IT2F-AHP) and Complex Proportional Assessment of Alternatives (COPRAS). The former captures a high degree of uncertainty due to the subjective weight assignment by the experts, while the latter calculates aggregate scores for 30 cities. Finally, we conduct posthoc analyses to examine the significance of the urbanization policies in Turkey on the SCI scores. Thus, the study provides valuable insights into urbanization practices and encourages local administrations to spend more effort balancing the benefits and costs of public policies on sustainability.

COPRAS method based on interval-valued hesitant Fermatean fuzzy sets and its application in selecting desalination technology

This paper firstly introduces the idea of interval-valued hesitant Fermatean fuzzy set (IVHFFS). It is one of the significant theoretical and practical features, which derive from the integration of hesitant Fermatean fuzzy set (HFFSs) and interval number. In this study, we firstly present the basic concept, various operations and distance measures of IVHFFSs. Then, based on the operations of IVHFFSs, some aggregation operators (AOs) are proposed for aggregating the interval-valued hesitant Fermatean fuzzy information. Furthermore, some elegant properties of these operators are discussed in detail. To show the applicability, we discuss a decision analysis process on IVHFFSs environment with the help of conventional complex proportional assessment (COPRAS) methodology. Finally, the selection process of desalination technology for treating the feed water is also taken to validate the developed decision analysis procedure on IVHFFSs. This paper considers various criteria and sub-criteria in the assessment procedure and determines the most significant criteria influencing the desalination technology selection process are technical, social, environment and economic criteria, with significance weights of 0.3972, 0.289, 0.1653 and 0.1486, respectively. The work concludes that the reverse osmosis (RO) is the suitable desalination technology under the considered criteria followed by electrodialysis (ED), and multiple-effect distillation (MED). Moreover, the sensitivity investigation and comparative study are presented to verify the robustness and stability of the proposed method. The findings of this study show that the proposed model can suggest more feasible performance while facing several input uncertainties and influencing factors.

Selection for additive manufacturing using hybrid MCDM technique considering sustainable concepts

PurposeIn the present scenario, the demand for additive manufacturing (AM) has increased. Taking into account environmental problems and sustainability, manufacturers are now also considering the environmental and sustainability criteria in their decision-making process. The sustainability concept is known as the triple-bottom line, namely, economic, social and environmental perspectives. Sustainable concept selection in the manufacturing organisation can be considered as the selection of sustainable material, product design, process, method and technology. This study aims to select an appropriate AM process by considering sustainability from various available techniques.Design/methodology/approachAppropriate sustainable performance indicators for the AM were identified based on literature as well as in discussion with experts and decision-makers. The model addresses all the major dimensions of sustainable concepts of AM such as material/product quality, machine performance, market stability, total cost and ecological values. A hybrid multi-criteria decision-making approach, i.e. stepwise weight assessment ratio analysis and complex proportional assessment methods, have been used to select the best AM technique. While selecting criteria affecting AM machines and processes, criteria based on the sustainable concept are considered.FindingsAmong the four selected AM processes, i.e. fused diffusion modelling (FDM), laminated object manufacturing (LOM), stereolithography apparatus (SLA) and selective laser sintering (SLS), the best alternative was found to be FDM.Research limitations/implicationsThe present study highlights some limitations in the selection of AM process and methodology used in this research. This study considers only four AM processes, i.e. FDM, LOM, SLA and SLS. Future work may include considering other AM processes and criteria that affect the sustainability of AM.Practical implicationsThe present work will help researchers and production managers to decide the best AM alternatives to fabricate desired parts. Hence, AM can help in maximum energy utilisation, optimal consumption of resources, minimum material wastage and reduction of CO2 emission.Originality/valueThe study considers some important criteria, including energy consumption, eco-friendly and wastage-free production, that help sustainable AM. This study can result in a good economic efficiency of AM industries and, therefore, positively impact customers using green products.

Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach)

The supplier selection problem (SSP) is a significant issue in renewable supply chain management (RSCM). Selecting a strategic green supplier can not only discover the sustainable development of supply chains but also optimize the consumption rate of resources and decrease the negative environmental effects, which adopts to the green development context. As a multiple criteria group decision-making (MCGDM) problem, choosing a strategic green supplier is important to renewable supply chains. However, how to choose a strategic green supplier for supply chains is a great effort. Hence, In the present work, evaluating a set of strategic suppliers is primarily based on green capabilities by using an integrated fuzzy Best Worst Method (FBWM) with the other two techniques, namely COPRAS (Complex Proportional Assessment of Alternatives) and WASPAS (Weighted Aggregated Sum-Product Assessment). Initially, nine strategic supplier selection criteria have been identified through literature review and a real-world case study of Iran's renewable energy supply chain is deliberated to exhibit the proposed framework's applicability. The applied methodology and its analysis will provide insight to decision-makers of strategic supplier selection. It may aid decision-makers and the procurement department in differentiating the significant strategic green supplier selection criteria and assess the strategic green supplier in the local and global market supply chain. Finally, the strengths and limitation of the framework are discussed by using comparative analysis with other methods.

A sustainability assessment framework for the high street

High street decline is a topic that has received a great deal of political and media attention within the last decade in the UK. External factors, such as the growth in online retail and changing economic conditions, have contributed to the shift in consumer needs and expectations, while many high streets have struggled to sustain the pace of the change. The sustainability of high street is influenced by a range of complex economic, environmental and social factors. As consumer needs and expectations increasingly favour social and experiential high street functions, the need to review the perception of high street success is vital. Here we identify, characterise and evaluate a set of criteria that can be used to assess the high street sustainability. By conducting the survey amongst professional experts and residents, the significance of these criteria is determined. Through the application of multiple criteria decision making (MCDM) method COmplex PRoportional ASsessment (COPRAS), the sustainability of several towns' high streets in England is assessed. Altogether, this study for the first time develops a sustainability assessment framework for the high street. It can be used to assist policy makers and key stakeholders in making effective decisions regarding the allocation of resources and identifying locations that require investment and development. The sustainability assessment framework for the high street can assist in achieving national and global commitments for the sustainable development.

Use of hybrid MCDM methods for site location of solar-powered hydrogen production plants in Uzbekistan

Uzbekistan is a developing country where energy demand is rising, and it has many problems in the energy supply sector. This issue leads to a mismatch between energy consumption and supply in this country. Most of the country’s energy supply comes from natural gas. A major part of Uzbekistan’s energy demand can be provided by solar power. The purpose of this study is to determine the position of using solar energy to generate hydrogen in 13 provinces of Uzbekistan. This study is performed by using the Stepwise Weight Assessment Ratio Analysis (SWARA) for criteria weighting and using the Weighted Aggregated Sum Product Assessment (WASPAS), the COmplex PRoportional Assessment of alternatives (COPRAS), the Evaluation Based on Distance from Average Solution (EDAS), and the Weight Sum Model (WSM) for ranking locations. The results of criteria weighting with SWARA show that the top three most important criteria are solar radiation, sun hours, and average wind speed with weights of 0.248, 0.2, and 0.154, respectively. All ranking methods identify Bukhara province as the most suitable place in Uzbekistan for solar-powered hydrogen production. It is estimated that 1539.2 MW of solar power and 24.92 tons of hydrogen are produced annually in Bukhara.

An Integrated Variance-COPRAS Approach with Nonlinear Fuzzy Data for Ranking Barriers Affecting Sustainable Operations

Sustainability is becoming the core theme of every organization to protect the planet from the drastic effects of climate change. Many organizations have drastically changed their practices to encourage green habits for sustainable operations. Practitioners have discussed the difficulties in the literature owing to the adoption of sustainable aspects of environmental, economic and social paradigms in the organization. One can identify diverse barriers, and ranking them would help policy-makers plan their actions. Motivated by this claim, a new integrated approach with nonlinear fuzzy data is put forward in this paper. The nonlinear mapping of fuzzy data provides a better representation of uncertainty, which inspired the authors to use nonlinear data. Further, the attitudinal variance method is proposed for a weight assessment of the criteria that can handle hesitation effectively and consider each agent’s reliability. The Boran principle in the nonlinear context is used to calculate the reliability values. Complex proportional assessment (COPRAS), a popular ranking algorithm, is extended to nonlinear data for rationally ranking barriers that affect sustainable operations. An illustrative example exemplifies the usability of the approach, and a comparison/sensitivity analysis reveals the pros and cons of the framework.

Optimum harnessing of solar energy with proper selection of phase changing material using integrated fuzzy-COPRAS Model

ABSTRACT Thermal Energy Storage (TES) devices can assist in storing the energy during the sunlight hours which can be used later on non-availability of solar power. Implementation of Phase Changing Material (PCM) can enhance efficiency of TES devices. Selection of resourceful and efficient PCM plays an essential role such that it can be successfully implanted nearly with all solar thermal devices. Assortment of the material involves selection of certain characteristics and properties associated with the performance of material as well as their physical, mechanical, economic and environmental properties. This study deals with a methodological analysis by integrating techniques for finding optimum PCM among various selected materials. Hybridization involves integrating Triangular Fuzzy Number (TFN) with Complex Proportional Assessment (COPRAS) method. In general, Fuzzy set comprises of three or more numbers, denoting it as TFN, Gaussian Fuzzy numbers, Trapezoidal Fuzzy Numbers, and so on. Although alternatives are many to design a fuzzy set depending on elements count, the TFNs are the ones considered as actual representations of a Fuzzy number. COPRAS is a well-known robust MCDM technique chosen to carry out the work of selection. Eight PCM have been compared on the parameters like Latent Heat, Cost, Melting points and others. Calcium Chloride Hexahydrate is the optimum material found as PCM. The result of this study would help planners and designers for an optimum selection of PCM in efficient harnessing of solar energy.

Smart Urban Mobility System Evaluation Model Adaptation to Vilnius, Montreal and Weimar Cities

To date, there is no developed and validated way to assess urban smartness. When evaluating smart city mobility systems, different authors distinguish different indicators. After analysing the evaluation indicators of the transport system presented in the scientific articles, the most relevant and influential indicators were selected. This article develops a hierarchical evaluation model for evaluating a smart city transportation system. The indicators are divided into five groups called “factors”. Several indicators are assigned to each of the listed groups. A hybrid multi-criteria decision-making (MCDM) method was used to calculate the significance of the selected indicators and to compare urban mobility systems. The applied multi-criteria evaluation methods were simple additive weighting (SAW), complex proportional assessment (COPRAS), and technique for order preference by similiarity to ideal solution (TOPSIS). The significance of factors and indicators was determined by expert evaluation methods: the analytic hierarchy process (AHP), direct, when experts evaluate the criteria as a percentage (sum of evaluations of all criteria 100%) and ranking (prioritisation). The evaluation and comparison of mobility systems were performed in two stages: when the multi-criteria evaluation is performed according to the indicators of each factor separately and when performing a comprehensive assessment of the smart mobility system according to the integrated significance of the indicators. A leading city is identified and ranked according to the smartness level. The aim of this article is to create a hierarchical evaluation model of the smart mobility systems, to compare the smartness level of Vilnius, Montreal, and Weimar mobility systems, and to create a ranking.

Blockchain Technology Application Challenges in Renewable Energy Supply Chain Management.

With the advent of new technologies and globalization of business, supply chains have turned into indispensable tools for gaining competitive advantage. The application of new technologies like blockchain can benefit sustainable energy supply chains by improving chain and logistics operations in the areas of trust, transparency and accountability, cooperation, information sharing, financial exchanges, and supply chain integration. However, the efforts to adopt such technologies in supply chains tend to face many challenges and challenges, which can seriously threaten their success. Therefore, it is crucial to carefully examine the challenges to blockchain technology application. This research focuses on identifying the criteria and challenges to the application of blockchain in renewable energy supply chains and also ranks the identified challenges in terms of their capacity to disrupt the process. The applicability of the suggested structure is examined in a case study of the renewable energy supply chain of Iran. In this study, the challenges are evaluated and ranked by the hybrid developed methods by the integration of the concept of gray numbers into the gray stepwise weight assessment ratio analysis (SWARA-Gray) and the gray evaluation based on distance from average solution (EDAS-Gray). Another group of hybrid methods including the gray weighted sum method (WSM-Gray), the gray complex proportional assessment (COPRAS-Gray), and the gray technique for order of preference by similarity to ideal solution (TOPSIS-Gray) is used to validate the results. The rankings obtained from all of these techniques show high degree of correlation. Among the identified challenges, "high investment cost" is found to be the most important challenge to the application of blockchain in sustainable energy supply chains.

Pythagorean fuzzy entropy measure-based complex proportional assessment technique for solving multi-criteria healthcare waste treatment problem.

With the increasing risk to human health and environmental issues, the selection of appropriate management and treatment of healthcare waste has become a major problem, especially in developing countries. There are various alternatives to dispose of health care waste. The important is to assess the best alternative among them. The assessment of each alternative should be done based on public health, psychological, economic, environmental, technological, and operational aspect. The selection of the best health care waste treatment (HCWT) alternative is a complicated, multi-criteria decision-making (MCDM) problem involving numerous disparate qualitative and quantitative features. Hence, in this research article, the MCDM method is presented for estimating and choosing the best alternative of HCWT by COPRAS technique in a Pythagorean fuzzy set (PFS). Here, in this paper, first of all, a new entropy measure on PFSs is proposed and its validity is studied. Thereafter, the MCDM technique Complex Proportional Assessment (COPRAS) is discussed in which the criteria weights are assessed by the proposed entropy measure and score function to enhance an efficacy and efficiency of the proposed technique. Furthermore, the above-defined technique is employed to resolve the real-life problem to obtain the best treatment alternative to disposal of the health care waste. Finally, sensitivity analysis is presented to rationale the proposed viewpoint for prioritizing HCWT alternatives.

Selection of Optimal Locations for Electricity Generation Using Concentrated Solar Power Technologies in Ghana

The selection of an optimum location for the installation of a Concentrated Solar Power (CSP) plant is very vital to its overall performance. Any selected location should suitably satisfy some favourable selection criteria such as high direct normal irradiance, high ambient temperature, lower wind speed, lower level of cloud cover and availability of a source of water. In this paper, the selection of an optimal location(s) for a CSP plant in Ghana is achieved using the Analytical Hierarchy Process (AHP) for the weighting of the selected criteria and then using a set of Multi-Criteria Decision-Making (MCDM) methods for the ranking of the various alternatives. The MDCM methods used in this work include the Vise Kriterijumsa Optimizacija I Kompromisno Resenje (VIKOR), Technique for Order of Performance by Similarity to Ideal Solution (TOPSIS), and Complex Proportional Assessment (COPRAS). The results indicate that VIKOR and COPRAS gave very closely related rankings while some of the rankings for the COPRAS were not closely related as compared to the other two methods. However, all three methods ranked Bawku, a town in the Upper East region of Ghana, as the most suitable location for the installation of a CSP plant. The other suitable locations, i.e., Navrongo, Yendi, Wa, Bolgatanga and Savelugu, for the installation of a CSP plant are in the northern part of the country.

Evaluation of Network Security Service Provider Using 2‐Tuple Linguistic Complex q‐Rung Orthopair Fuzzy COPRAS Method

In recent years, network security has become a major concern. Using the Internet to store and analyze data has become an integral aspect of the production and operation of many new and traditional enterprises. However, many enterprises lack the necessary resources to secure information security, and selecting the best network security service provider has become a real issue for many enterprises. This research introduces a novel decision‐making method utilizing the 2‐tuple linguistic complex q‐rung orthopair fuzzy numbers (2TLCq‐ROFNs) to tackle this issue. We propose the 2TLCq‐ROF concept by combining the complex q‐rung orthopair fuzzy set with 2‐tuple linguistic terms, including the fundamental definition, operational rules, scoring, and accuracy functions. Aggregation operators are the fundamental mathematical approach used to combine various inputs into a single output. Taking into account the interaction between the attributes, we develop the 2TLCq‐ROF Hamacher (2TLCq‐ROFH) operators by using the innovative operational rules. These operators include the 2TLCq‐ROFH weighted average (2TLCq‐ROFHWA), 2TLCq‐ROFH ordered weighted average (2TLCq‐ROFHOWA), 2TLCq‐ROFH hybrid average (2TLCq‐ROFHHA), 2TLCq‐ROFH weighted geometric (2TLCq‐ROFHWG), 2TLCq‐ROFH ordered weighted geometric (2TLCq‐ROFHOWG), and 2TLCq‐ROFH hybrid geometric (2TLCq‐ROFHHG) operators. In addition, we talk about the properties of 2TLCq‐ROFH operators such as idempotency, commutativity, monotonicity, and boundedness and also examine their spatial cases. To tackle the problems of the 2TLCq‐ROF multiattribute group decision‐making (MAGDM) environment, we develop a novel approach according to the COPRAS (complex proportional assessment) model. Finally, to validate the feasibility of the given strategy, we employ a quantitative example related to select the best network security service provider. In comparison with existing approaches, the developed decision‐making algorithm is most extensively used and reduces the loss of information.