Complex Proportional Assessment Research Articles

A Comprehensive Guide to the COPRAS method for Multi-Criteria Decision Making

MCDM has been utilized as a proficient decision-making technique for numerous decades. Complex Proportional Assessment (COPRAS) method, a prominent technique in multi-criteria decision-making (MCDM) which offers a systematic and effective framework for evaluating alternatives and making informed choices. The versatility of COPRAS is demonstrated via case studies across various domains, such as engineering, business, and environmental management, showcasing its adaptability and robustness in providing solutions to diverse decision-making scenarios. There is a lack of a comprehensive guide and a reviewing of application, strengths, and limitation for this method in the literature. Therefore, this study aims to offer an in-depth understanding of the COPRAS approach, including its applications, advantages, and disadvantages. Additionally, it provides detailed guidance on how to utilize the COPRAS methodology for decision-making and real-life problems.

Multi-Criteria Assessment of Timber-Based Structural Systems for a Grocery Store

To reduce the negative impact on the environment, architects, designers, and construction companies need to find and apply eco-friendly and sustainable building solutions. Due to its renewable nature and numerous advantages, timber has become an attractive substitute for steel and concrete in both residential and non-residential construction projects. However, timber application in the construction of grocery stores is a relatively new concept. The purpose of this research is to propose three alternative timber-based structural systems for a grocery store in Lithuania and to select the most efficient option based on multi-criteria decision-making methods. Three alternative glued laminated timber (glulam) structural systems—the glulam column and truss system, the glulam three-hinge frame system, and the glulam column and double-tapered beam system—were designed. The systems were evaluated against ten criteria, reflecting structural properties, cost efficiency, assembling complexity, and aesthetics. Multiple-criteria assessments by the COmplex PRoportional ASsessment (COPRAS) method and simple additive weighting (SAW) method revealed that the best-performing alternative is the glulam column and double-tapered beam system due to the lower cost of load-bearing structures, the smaller quantity of required steel details and fittings, and the highest maximum utility ratio according to serviceability limit states compared to other alternatives.

Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values

This paper delves into the development and validation of the RAMDOE method, a pioneering approach in multi-criteria decision making (MCDM) that seamlessly integrates the root assessment method (RAM) and design of experiments (DOE) techniques, addressing the inflexibility of traditional MCDM methods in accommodating adjustments in criteria ranges and the addition of new alternatives without necessitating a complete overhaul of the decision framework. Through empirical analysis, the study demonstrates the RAMDOE method's remarkable efficacy in precisely ranking alternatives, as illustrated through a practical case study focused on the selection of a supplier from a pool of seven candidates. One of the most notable aspects of the RAMDOE method lies in its capacity to formulate a regression equation that accurately captures the intricate relationship between alternative scores and criteria values, enabling decision-makers to seamlessly integrate new alternatives into the decision-making process without the cumbersome task of recalibration, thereby distinguishing it from conventional MCDM techniques such as TOPSIS (technique for order of preference by similarity to ideal solution), COPRAS (complex proportional assessment), MOORA (multiobjective optimization on the basis of ratio analysis), EDAS (evaluation based on distance from average solution) and CODAS (combinative distance-based assessment). The practical implications of these findings are profound, offering decision-makers across various domains a more efficient and adaptable framework to navigate complex decision scenarios. Particularly in contexts like supplier selection, where criteria ranges may vary significantly, the RAMDOE method provides decision-makers with a robust toolset to make informed decisions, presenting a promising avenue for addressing the dynamic nature of decision-making environments and enhancing the overall robustness and flexibility of MCDM processes in real-world applications

GHF-COPRAS Multiple Attribute Decision-Making Method Based on Cumulative Prospect Theory and Its Application to Enterprise Digital Asset Valuation

With the rapid development of the economy, data have become a new production factor and strategic asset, enhancing efficiency and energy for technological innovation and industrial upgrading in enterprises. The evaluation of enterprise digital asset value (EDAV) is a typical multi-attribute decision-making (MADM) problem. Generalized hesitant fuzzy numbers (GHFNs) can better express the uncertainty and fuzziness of evaluation indexes, thus finding wide applications in MADM problems. In this paper, we first propose the Kullback–Leibler (K-L) divergence distance of GHFNs and prove its mathematical properties. Second, recognizing that decision-makers often have finite rationality in practical problems, we combine the cumulative prospect theory (CPT) with the Complex Proportional Assessment (COPRAS) method to propose the GHF-CPT-COPRAS model for solving MADM problems. Simultaneously, we extend the distance correlation-based Criteria Importance Through Intercriteria Correlation (D-CRITIC) method to the GHF environment to rationally calculate the weights of attributes in the EDAV evaluation problem. Finally, we apply the proposed GHF-CPT-COPRAS model to the EDAV evaluation problem and compare it with existing GHF decision-making methods to verify its effectiveness and feasibility. This study provides an important reference for addressing the EDAV assessment problem within an uncertain fuzzy environment and extends its application methods in the decision-making field.

Bloodmobile location selection for resilient blood supply chain: a novel spherical fuzzy AHP-integrated spherical fuzzy COPRAS methodology

PurposeBlood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.Design/methodology/approachThis study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.FindingsThe results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.Practical implicationsThis study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.Originality/valueThis study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

An integrated Bi-objective green vehicle routing and partial disassembly line problem for electronic waste: an industrial case study

ABSTRACT Today, serious environmental problems arise with overconsumption. The most effective way of protecting the environment is recycling. To obtain maximum benefit from the recycling activities depends on the effective and robust design of the disassembly lines. In addition, the distribution plan of products to be recycled is as important as the disassembly process. Therefore, this study includes the integrated optimization of the partial disassembly line balancing problem and the multi-objective green vehicle routing problem for the first time. The integrated problem is formulated as a Multi-Objective Mixed Integer Linear Programming. The model’s objectives consist of minimization of total CO2 emission and cost. The Pareto optimal solution set is found by solving this problem with the Augmented ℇ-Constraint Method. The model respectively determines (i) the total number of opened workstations in the disassembly center, (ii) optimal task assignments to workstations in disassembly centers and non-disassembled tasks, (iii) total workstation times and idle times of each workstation, (iv) optimal distribution routes for all vehicles. This study examines a case study in Turkey. To determine the best Pareto optimal solution for homogeneous and heterogeneous fleets, the integrated multi-criteria decision-making method consisting of EWM (Entropy Weight Method) and COPRAS (Complex Proportional Assessment) is used.

An integrated CRITIC-COPRAS approach for multi-response optimization on AWJM of hybrid filler–reinforced polymer composite and its surface integrity

Composites have gained acceptance in an extensive range of applications owing to their unique characteristics. But, machining of these materials is often challenging due to improved bonding between matrix and fibre when fillers are added. Since the machinability is an important aspect for any material for its successful utilization, it is essential to analyse the effect of secondary phase on machinability. However, investigations on the effect of fillers on machinability of polymer composites are minimal. In this research, hybrid fillers, namely boron nitride (BN) and montmorillonite (MMT) nanoclay, were added to epoxy/glass fibre composite through compression moulding, in which quantity of MMT is fixed and BN is varied from 2 to 6 wt%. Abrasive water jet machining (AWJM) is a leading method for machining polymer composites in which transverse speed, stand-off distance, pump pressure and filler percentage are key factors and are considered as input variables. To assess the machinability, material removal rate (MRR), surface roughness (Ra) and kerf taper (Kt) are chosen as response variables. Experimental planning is done through Taguchi method, and Criteria Importance Through Intercriteria Correlation (CRITIC)-weighted Complex Proportional Assessment (COPRAS) technique is utilized for optimization. The results revealed that addition of BN reduces the MRR while it improves the surface finish and reduces the Kt. Transverse speed has the most influence over all the considered output responses, stand-off distance and water pressure mainly affect the MRR and Ra while filler addition mainly affects the Kt. The hybrid CRITIC-COPRAS approach–recommended optimal control factors resulted in 16.20 mm3/min MRR with 0.29° Kt and 3.86 µm Ra. The recommended optical condition can be utilized for effective machining of polymer composite with MMT/BN fillers.Graphical abstract

A Hybrid Group Multi-Criteria Approach Based on SAW, TOPSIS, VIKOR, and COPRAS Methods for Complex IoT Selection Problems

The growth of Internet of Things (IoT) systems is driven by their potential to improve efficiency, enhance decision-making, and create new business opportunities across various domains. In this paper, the main selection problems in IoT-type systems, criteria used in multi-criteria evaluation, and multi-criteria methods used for solving IoT selection problems are identified. Then, a Hybrid Group Multi-Criteria Approach for solving selection problems in IoT-type systems is proposed. The approach contains the Best Worst Method (BWM) weighting method, multi-criteria Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Complex Proportional Assessment Method (COPRAS), and a method that combines the solutions obtained using the four considered multi-criteria methods to obtain a single solution. The SAW, TOPSIS, VIKOR, and COPRAS methods were analyzed in relation to their advantages, disadvantages, inputs, outputs, measurement scale, type of normalization, aggregation method, parameters, complexity of implementation, and interactivity. An application of the Hybrid Group Multi-Criteria Approach for IoT platform selection and a comparison between the SAW, TOPSIS, VIKOR, and COPRAS solutions and the solution of the proposed approach is realized. A Spearman correlation analysis is presented.

Comprehensive evaluation of energy absorption characteristics of Al‐CFRP hybrid tube under radial impacts

AbstractThis paper aimed to investigate the energy absorption characteristics and damage mechanism of carbon fiber reinforced plastics/aluminum (Al‐CFRP) under radial impact. In this study, the damage mode of the hybrid tube is analyzed by falling hammer impact experiments, and the correctness of the finite element model is verified by comparing the experimental and numerical simulation results. Then, the damage mechanism of the hybrid tube under impact loading and the effects of the increase of the fiber angle, the wall thickness of Aluminum, and the number of outer CFRP layers on the impact resistance were analyzed according to the model. The comprehensive performance model of the hybrid tube was established by using the complex scale comprehensive evaluation method, and the genetic algorithm was used to optimize the hybrid tube and determine its optimal performance under radial impact load. The results show that the Al‐CFRP hybrid tube's overall stiffness and deformation resistance under radial impact is improved with the increase of the fiber angle, the wall thickness of the Al tube, and the number of outer CFRP layers. Combined with the parametric analysis of the numerical simulation results, a comprehensive performance evaluation model based on the complex proportionality assessment method (COPRAS) was developed and a genetic algorithm (GA) under back propagation (BP) neural network prediction was used. The optimal hybrid tube form with the best overall performance under radial impact was obtained using GA with BP neural network prediction.Highlights The energy absorption characteristics of hybrid tubes under radial impact are investigated A comprehensive performance evaluation model of hybrid pipe based on the complex proportional assessment method (COPRAS) is developed The failure process and energy absorption mechanism of the hybrid pipe under radial impact are analyzed A genetic algorithm (GA) with backpropagation (BP) neural network prediction was used to obtain the hybrid pipe form with the best overall performance under radial impact

Multiple attribute decision making using an enhanced complex proportional assessment method based on probabilistic generalized orthopair fuzzy soft sets

Multiple attribute decision making using an enhanced complex proportional assessment method based on probabilistic generalized orthopair fuzzy soft sets

Decision support system in determining the location of new supermarket branches using the copras method

Supermarkets are one of the ideal and profitable retail business sectors to try because they are located in various urban and rural areas. This causes many people to be interested in setting up a supermarket. However, determining a strategic location is not easy and requires many strategic location considerations. The research objective is to develop a Decision Support System (DSS) to determine the location of new supermarket branches using the Complex Proportional Assessment (COPRAS) method, which is expected to be helpful for management and supermarket partners as a business strategy. The COPRAS method excels in calculating alternative utilities and selecting the best alternative. There are nine criteria (land rental price, distance to competitors, security, distance to education, warehouse distance, cleanliness, land area, building price, crowd) and five alternative locations (Juanda, Hos Cokroaminoto, Bayangkara, Batoro Katong, Sumoroto) are considered. This research created a web-based DSS that selects the best location for supermarket, with Juanda (A1) ranked first and scored 100, followed by Somoroto (location A5) with a score of 99.861, Bayangkara (A3) with a score of 97.099, Batoro Katong (A4) with a score of 91.293, and HOS Cokroaminoto (A2) with a score of 88.877. From the results of the COPRAS calculation, it can be concluded that Juanda is the best location to build a new supermarket branch location. This result provides a valuable tool for management and supermarket partners seeking to make informed decisions about branch expansion strategies.

A Novel Trigonometric Entropy Measure Based on the Complex Proportional Assessment Technique for Pythagorean Fuzzy Sets

The extension of intuitionistic fuzzy sets (IFS) to Pythagorean fuzzy sets (PFS) is a significant advancement, addressing the inherent limitations of IFS. This study introduces a novel entropy measure specifically designed for Pythagorean fuzzy sets, establishing its axiomatic definition and presenting key properties. Decision making guided by entropy is advantageous, as it effectively mitigates ambiguity with increasing entropy values. Furthermore, a numerical example is provided to facilitate a comparative assessment of our newly introduced entropy measure in contrast to existing PFS entropy measures. The validation of our findings is achieved through the application of the COPRAS method, which determines decision outcomes based on a multitude of influencing factors. Notably, the determination of weights in this method is underpinned by the utilization of our innovative entropy measure.

Eco-performance evaluation of product designs – an integrated fuzzy complex proportional assessment with life cycle assessment

ABSTRACT The growing public awareness has driven enterprises to develop environmentally friendly designs to fulfill customer satisfaction. Some eco-design tools have been introduced to designers to support greener product design and development qualitatively. However, most require qualitative judgement during the evaluation process. Although life cycle assessment (LCA) helps quantify a product system’s environmental loads, it requires much time and resources for data collection. Design selections are not preferred during the early product development stage, especially when the product development schedule is rather tight nowadays. This paper proposes a practical approach integrating a fast-track LCA, fuzzy-set, with COmplex PRoportional ASsessment (COPRAS). This paper proposes an approach by incorporating the fuzzy-set, COPRAS, and LCA for decision-makers to evaluate design alternatives at the early product development stage. The originality of the paper is to provide an efficient approach to evaluating various design alternatives by quantifying their corresponding environmental burdens using LCA and fuzzy-set. Three distinct features can be found in the proposed generic approach. This study brings two contributions to the related field. For the area related to environmental impact assessment, this study illustrates the applicability of LCA in conjunction with COPRAS and fuzzy-set for the design alternative selection. Decision-makers can apply the proposed method that in-depth knowledge of environmental impact assessment is not essential, and the qualitative input required is minimal compared to a comprehensive LCA study.

A comparative study of original equipment manufacturer brake pads using tribological testing and hybrid ranking for enhanced decision making and cost effectiveness

Tribological test and hybrid ranking techniques are employed to evaluate brake pads from original equipment manufacturers for Indian passenger cars. The study was conducted for four brake pads designated as OE1, OE2, OE3, and OE4. The assessment integrates the analytical hierarchy process with various ranking methods including Extension Evaluation Method, Complex Proportional Assessment, Preference Selection Index, and Technique for Order of Preference by Similarity to Ideal Solution. Brake pad samples undergo testing according to the standard IS2742 part 1-4 of 1994, generating crucial performance parameters such as performance coefficient of friction, hot coefficient of friction, normal coefficient of friction, fade percentage, recovery percentage, variation in coefficient of friction, wear thickness loss percentage, wear mass loss percentage, and time taken to reach maximum temperature. These performance metrics are technically analyzed and ranked using hybrid ranking techniques to enhance the decision-making process. The results show that OE4, a budget-friendly brake pad ranked first, is the best performer. OE2, a more expensive alternative, is placed second, and OE1 and OE3, which are more affordable possibilities, are ranked third and fourth, respectively. This research serves as a valuable resource for selecting brake pads for Indian passenger cars, especially in scenarios where technical specifications and cost-effectiveness are crucial considerations.

Impact resistance of horsetail bio-honeycombs

Inspired by the ingenious cross-sectional structure of horsetail stems, a group of novel horsetail bio-honeycombs (HBHs) are firstly proposed to pursuit a superior impact resistance performance. The out-of-plane impact resistance characteristics and mechanical properties of the proposed HBHs are investigated by means of test, theoretical analysis, and finite element (FE) analysis. In the process of deriving the theoretical model of HBHs, the novel 5-panel and 7-panel membrane energy dissipation corner elements are firstly proposed and reasonable theoretical solutions for them are obtained. Theoretical results suggest that the errors between numerical and theoretical results for the majority of the HBHs are within 7 %. In addition, the studies indicate that the HBHs outperform the circular honeycomb (CH) in terms of crashworthiness while ensuring that their relative densities are the same. The complex proportional assessment method is utilized to evaluate the crashworthiness of HBH_n_6_1.5 (n represents the number of ribs, 6 represents the size of the outer diameter, and 1.5 represents the ratio (ζ) of the outer diameter to the inner diameter) under the same relative density. Furthermore, results suggest that energy absorption and crushing force efficiency of HBH_16_6_1.5 are 31.31 % and 25.54 % higher than those of CH, respectively. Subsequently, the influences of geometric parameters, including the ζ and the thickness-to-cell length ratio (TL), on the impact resistance of HBH_16_6_1.5 are investigated thoroughly. The findings show that when the ζ is within 1.2–1.5, the HBHs can exert their maximum potential, in which the inner diameter of HBHs is close to its outer diameter. Also, the findings demonstrate that the HBHs will undergo three distinct deformation modes. When the TL is roughly within 0.0200–0.0267, the deformation of HBHs will be in the transition deformation mode.

Risk ranking of rig up operation activities using multi-criteria decision-making methods based on fuzzy environment

The main aim of this research study is to determine the risk ranking of 29 failure modes of rig-up operations using a well-known and highly effective MCDM method i.e. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). This method takes into account the four criteria which comprise human impact, property damage, environmental effect and company reputation as risk criteria. Three Experts in the field were invited to present the risk ranking of the relative importance of criteria and criteria performance of each risk (as failure mode) by utilizing linguistic variables which are then integrated in triangular fuzzy numbers for further analysis using the Fuzzy TOPSIS method. The evaluation concluded that FM20 (Collision between the offshore platform and boats) is the most dangerous risk with a coefficient of closeness (CCi) equal to 0.992 while the risk level of FM26 (foggy weather) was found least having a coefficient of closeness (CCi) of 0. Subsequently, sensitivity analysis of ranks concluded that FM1 (H2S inaccurate monitoring) is the most sensitive alternative with standard deviation and frequency of rank change was 5.16 and 15 respectively whereas FM20 (Collision between offshore platform and boats) is observed to be the least sensitive alternative. Fuzzy TOPSIS results were found in excellent correlations with the other reliable MCDM methods which include Fuzzy VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) and Fuzzy COPRAS (COmplex PRoportional ASsessment) yielding correlation of around 1. This study proves to be a landmark in the petroleum industry and significantly contributes to verifying safe practices, by taking appropriate actions in minimizing the risk level associated with different activities during rig-up operations.

An integrated model for rice supplier selection strategies and a comparative analysis of fuzzy multicriteria decision-making approaches based on the fuzzy entropy weight method for evaluating rice suppliers.

Rice, being a staple food in many countries, necessitates the identification of reliable suppliers to ensure a steady supply. Consequently, it is vital to establish trustworthy vendors for various types of this essential grain who can meet stringent product quality standards. This study aims to identify, analyze, rank, and select primary rice suppliers. The study emphasizes the importance of selecting and managing suitable providers to meet customer demands, proposes a ranking model for rice suppliers, and introduces developed fuzzy MCDM techniques. It proposes an integrated model for selecting rice suppliers, considering factors related to the processes before, during, and after selecting providers within a defined framework. The outcomes shows that rice supplier selection strategy can efficiently identify reliable rice suppliers, improve buyer value, reduce procurement risk, enhance efficiency, and establish strong supply chain relationships in complex decision-making processes. To assess suppliers, the study introduces two advanced integrated approaches and compares them. The fuzzy entropy weight method (EWM) was used to determine the criteria weights. The ranking of rice suppliers was achieved using a fuzzy multi-objective optimization based on ratio analysis (MOORA), fuzzy complex proportional assessment (COPRAS), and combinations of these two methods in different approaches. The methodology supports decision-makers in a rapidly evolving global environment by assisting importers, traders, suppliers, procurement, and logistics management, particularly for non-rice-cultivating countries in rice importation and supplier selection. The numerical analysis is grounded in a real-world case study of selecting rice suppliers in Jordan. The findings reveal that the various strategies yield both similar and different results. Furthermore, the integrated method is considered the most accurate for evaluating rice imports and suppliers, aligning closely with the reality of the current situation.

CSsEv: Modelling QoS Metrics in Tree Soft Toward Cloud Services Evaluator based on Uncertainty Environment

Cloud computing (ClC) has become a more popular computer paradigm in the preceding few years. Quality of Service (QoS) is becoming a crucial issue in service alteration because of the rapid growth in the number of cloud services. When evaluating cloud service functioning using several performance measures, the issue becomes more complex and non-trivial. It is therefore quite difficult and crucial for consumers to choose the best cloud service. The user's choices are provided in a quantifiable manner in the current methods for choosing cloud services. Hence, this study attempts to achieve this objective through construction. decision-making framework so-called cloud services evaluator (CSsEv). The main indicator and its sub-indicators are formed as nodes at levels(n) in tree soft sets (TSSs). Thereafter Single Value Neutrosophic Sets (SVNSs) as branch of neutrosophic sets which conjunction with the Multi-Criteria Decision Making (MCDM) technique to facilitate analysis and evaluation process for the available Cloud services providers. Hence, entropy is employed to obtain indicators and sub_indicators’ weights and Complex Proportional Assessment utilizes these weights to facilitate the decision process of selecting optimal ClSPs.

Impacto da COVID-19 nas PMEs no Brasil e drivers de percepção gerencial: um novo modelo neural baseado em funções de utilidade ponderadas pela entropia

Abstract Departing from the inconclusive results of the scant literature on the COVID-19 impact on Small and Medium Enterprises (SMEs), this paper proposes a novel evaluation model for addressing this issue through managerial perceptions. Over 6000 SMEs responded to twelve rounds of surveys from 2020 to 2021 during the pandemic, allowing to track the evolution over time of the perceived impact of the pandemic on small businesses. A novel entropy-weighted utility function approach is proposed here, followed by artificial neural network regression to map the variables related to the SME’s businesses that most foster the perceived utility of each business criterion during the pandemic. First, weights of business-related criteria were computed using Stepwise Weight Assessment Ratio Analysis (SWARA), sorting their relative importance - or perceptions - based on information entropy ranks derived from questionnaires collected. Transfer entropy measurements also helped in unveiling the hidden cause-effect relationships among criteria. Second, business utility functions for each criterion were computed using Complex Proportional Assessment based on SWARA weights. Third, neural network regressions were used to explain the managerial perceptions on each business criterion during the pandemic, considering each business variable. Our expected and unexpected results suggest that more resilient SMEs in Brazil are 5-10 years old and operating in the services and construction sectors. Moreover, loan success is the second most impactful criterion, deeply impacting the continuity of economic activity levels, and it is not impacted by any other business criteria. Implications for policymakers and governmental actions are highlighted.

Utilizing an integrated AHP-COPRAS approach for battery selection in electric vehicles

Internal combustion engine vehicles provide better performance and longer-range using fossil fuels such as gasoline and diesel. However, fossil fuels are non-renewable and cause environmental pollution, alternative fuels such as blends of ethanol and biodiesel, hydrogen etc have been sought for these vehicles. On the other hand, some researchers prefer to design alternative vehicles such as hybrid and electrical vehicles, instead of changing the fuel type. Among the studied topics for alternative vehicles, the battery is one of the most important components, especially in electrical vehicles. Batteries are diversified with different criteria such as battery life, nominal voltage, energy density, volumetric energy density, specific power, operating temperature, and production cost. In this study, the expert perspective was utilized when selecting the battery type to be employed for the energy source through utilizing the Integrated Analytical Hierarchy Process (AHP) - Complex Proportional Assessment (COPRAS), a multi-criteria decision-making approach. Various batteries such as Lead-acid (Pb-acid), Nickel-cadmium (Ni-Cd), Ni-MH, Sodium Nickel Chloride (Zero Emission Battery Research Activity-ZEBRA), Lithium –Ion (Li-Ion) Battery were evaluated in terms of different criterion. Among the alternatives the Li-ion battery type is chosen as the best option and the Ni-Cd battery is the least chosen alternative.