Complex Proportional Assessment Method Research Articles

A novel BWM-entropy-COPRAS group decision framework with spherical fuzzy information for digital supply chain partner selection

AbstractThe transformation and upgrading of traditional supply chain models through digital technology receive widespread attention from the fields of circular economy, manufacturing, and sustainable development. Enterprises need to choose a digital supply chain partner (DSCP) during the process of digital transformation in uncertain and sustainable environments. Thus, the research constructs an innovative decision methodology for selecting the optimal DSCP to achieve digital transformation. The proposed methodology is propounded based upon the entropy measure, generalized Dombi operators, integrated weight-determination model, and complex proportional assessment (COPRAS) method under spherical fuzzy circumstances. Specifically, a novel entropy measure is proposed for measuring the fuzziness of spherical fuzzy (SF) sets, while generalized Dombi operators are presented for fusing SF information. The related worthwhile properties of these operators are discussed. Further, an integrated criteria weight-determination model is presented by incorporating objective weights obtained from the SF entropy-based method and subjective weights from the SF best worst method. Afterward, an improvement of the COPRAS method is proposed based on the presented generalized Dombi operators with SF information. Lastly, the practicability and validity of the proposed methodology are verified by an empirical study that selects an appropriate DSCP for a new energy vehicle enterprise to finish the goal of digital transformation. The sensitivity and comparative analysis are carried out to illustrate the stability, reliability, and superiority of the propounded methodology from multiple perspectives. The results and conclusions indicate that the propounded method affords a synthetic and systematic uncertain decision-making framework for identifying the optimal DSCP with incomplete weight information.

Integrated nonurban-urban flood management using multi-objective optimization of LIDs and detention dams based on game theory approach

Flood events in urban and non-urban areas have long-term devastating impacts on communities resulting in casualties and economic damages. Different interconnected concepts of flood management lead decision-makers to broaden their focus from traditional points of view to transcend the disciplinary boundaries of hydrological modeling. So, evaluating interconnected aspects of flood control requires configuring an Integrated Flood Management (IFM) system. In this research, a novel comprehensive framework is proposed to control floods in urban and non-urban areas using Low-Impact Development (LID) practices and detention dams, simultaneously. In the first step, urban and non-urban areas of the Darakeh catchment in Tehran, Iran, as the study area, are modeled using Storm Water Management Model (SWMM). Next, by coupling the SWMM with Pareto Envelope-based Selection Algorithm II (PESA-II), optimal management scenarios are generated considering four hydrological-economic objectives. Each management scenario specifies the optimal sites and dimensions of detention dams and the optimal location and area of LIDs in non-urban and urban areas, respectively. Indeed, the innovative IFM framework provides a multi-dimensional trade-off between upstream and downstream flood protection. Then, interactions among the main stakeholders with conflicting interests are incorporated into utility functions. Ultimately, using COmplex PRoportional ASsessment (COPRAS) and Nash bargaining methods the most capable management scenarios are selected based on stakeholders' preferences. Results showed that the IFM framework can be significantly effective in flood severity attenuation. Based on the findings, proposed method warrants peak flow reduction up to 60.04 and 53.50 percent at the inlet and outlet of the urban area. Besides, the Nash bargaining approach tends to select a scenario with a higher peak flow reduction compared to the COPRAS method. Also, results signify that each stakeholder's relative importance and preferences can remarkably impact the decision-making process. In addition to resolving conflicts arising from implementing flood control measures, this framework can incorporate divergent aspects of flood management into a reliable system.

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.

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.

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.

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.

A NEW METHODOLOGY FOR TREATING PROBLEMS IN THE FIELD OF TRAFFIC SAFETY: CASE STUDY OF LIBYAN CITIES

Traffic safety is an area of great importance, since there are many traffic accidents every day in which a significant number of people are killed. Defining certain strategies and identifying potentially the most dangerous towns and cities regarding this area are, on the one hand, a necessity, and, on the other hand, a challenge. In this paper, integrated Multi-Criteria Decision-Making (MCDM) model for ranking cities in Libya from the aspect of traffic safety has been proposed. The model implies a set of 8 criteria on the basis of which 5 decision-makers rated the 10 most deprived cities in Libya. The Full Consistency Model (FUCOM) in combination with the rough Dombi aggregator is used to determine the significance of the criteria. The Rough Simple Additive Weighting (R-SAW) method is used to rank the alternatives. The rough Dombi aggregator is also used for averaging in group decision-making while evaluating the alternatives. The stability of the model and the obtained results has been verified by the sensitivity analysis, which implies a 2-phase procedure. In the 1st phase, rough Additive Ratio Assessment (R-ARAS), Rough Weighted Aggregated Sum Product Assessment (R-WASPAS), Rough Complex Proportional Assessment (R-COPRAS) and Rough Multi-Attributive Border Approximation-area Comparison (R-MABAC) methods are applied. The 2nd phase implies changing the parameter ρ in the procedure of rough Dombi aggregator, while the 3rd phase includes the calculation of Spearman’s Correlation Coefficient (SCC) that shows a high correlation of ranks.

An integrated hybrid MCDM approach to evaluate countries’ COVID-19 risks

To enable planning and early reaction efforts, it is important to identify the nations most at risk from COVID-19's health and humanitarian effects, which could exceed present national response capabilities. INFORM COVID-19 Risk Index developed by European Commission is one of the initiatives to meet the aforementioned need. However, the Index has 40 conflicting and comprehensive indicators (e.g., health system capacity, hygiene, vulnerability) and different countries that lead to a need for multicriteria decision-making (MCDM) approaches. This paper offers an integrated MCDM approach with two phases to re-assess the countries' COVID-19 risks based on INFORM COVID-19 Risk Index. In the first phase, the 40 indicators are prioritized using the Entropy-based multi-choice best-worst method (MC-BWM) to provide multiple viewpoints for the preferences values. In the second phase, 29 countries from different geographical regions are ranked using the COPRAS (Complex Proportional Assessment) method. Applying these three methods together on the COVID-19 risk assessment of countries is the most significant novelty for the relevant literature. The proposed approach has undergone a thorough comparative evaluation with the released INFORM COVID-19 Risk Index, and recommendations are provided based on different scenario analyses.

MULTI-CRITERIA DECISION ANALYSIS USING COMPLEX PROPORTIONAL ASSESSMENTS AND RANK ORDER CENTROID METHODS IN THE SELECTION SYSTEM FOR TUTORING INSTITUTIONS

Tutoring can help increase students' self-confidence, reduce anxiety about tests or assignments, and overcome learning barriers. The large number of tutoring institutions that offer various programs makes parents or students have to be observant when choosing them. To choose a tutoring institution, parents or students must know all the profiles and programs of the institution to be selected. This creates a difficult and long time to come up with a choice. The purpose of this study is to use the Multi Criteria Decision Analysis (MCDA) approach through the Complex Proportional Assessment (COPRAS) method and the Rank Order Centroid (ROC) method to create a Decision Support System (DSS) that will make it easier to choose a tutoring institution. The ROC approach serves to determine the weight based on the order of importance of the criteria. The COPRAS method is used because this method takes utility into account by assessing the usefulness of each alternative. This research produced a web-based tutoring institution selection DSS that can provide alternative recommendations based on criteria determined by decision-makers. The results of system calculations and manual calculations do not show a different value, which shows that the system produces a valid COPRAS approach value. Based on the results of usability testing, the built DSS scored 89.17%; in other words, the system is feasible to use.

Penerapan Metode Copras dalam Pemilihan Kepala Pengendalian Mutu (Head Of Quality Control)

In the selection of the current Head of Quality Control is appointed manually based solely on the information provided in the application and the decisions that have been raised are inaccurate and cause delays causing the assessment not to be completed. In addition, when recruiting the Head of Quality Control manually, there are several things that can cause problems, such as hiring a Head of Quality Control who does not meet the criteria set by the company, carrying out a slow selection process, and others. The methodology used is the Complex Proportional Assessment (COPRAS) method, which is an approach used to collect data and develop systems and applications to assist companies in making decisions based on common problems. The calculation results with COPRAS were obtained from 10 selected employees, the highest UI score of 100 and the lowest of 52.18. Companies can find qualified managers who meet organizational standards by implementing a decision support system based on this COPRAS methodology.

Site suitability analysis using MacBeth and COPRAS in a case study of the cement industry under SCM implementation

In the past two years, 2020-2022, the developing construction industry has been a huge issue according to the negative effect of Covid-19 with the increasing pandemic situation in cities and areas. In Covid-19 pandemic situation, the cement manufacturing industry has been crucial and needed more scrutiny. As cement is the second significant component after water in concrete and construction industry. Meanwhile, locating a cement plant in a special area of the city is challenging and affecting more by local communities and other involved environmental factors. The location selection decisions need to grow by environmental, economic, technical and social attributes. This study aims to present the site suitability decisions through a case study of locating a new manufacturing plant for cement production in Tehran surrounding, Iran. In this process, some required technical and tactical criteria are deserved for evaluating and suitability of the plant through decision-makers for cement manufacturing. All the feasible industrial alternative locations were evaluated under various criteria and regarding the Covid-19 pandemic’s negative impact to identify the most appropriate location for the cement industry. The authors proposed two Multi-Criteria Decision Attributes (MCDA) methods of MacBeth and COmplex PRoportional ASsessment (COPRAS) to evaluate and select the most suitable location for site suitability of the cement plant in this problem. Though the MacBeth method does not need to calculate weights of the Geographical Information System (GIS) criteria, the COPRAS method determined and used BWM (Best-Worst Method) as the weighing method. In sum, the comparison of the two methods was obtained according to the given results and ranks of volunteer cement suppliers for site suitability of the cement plant.

Investigation on 1-Propanol Electronic mode of fumigation on diesel engine performance and emission Fueled with diesel and lemongrass biodiesel blend using AHP- COPRAS

The current experimental work investigated the engine performance and emissions when a compression ignition engine was powered by 1-propanol Electronic Mode (EM) fumigation with biodiesel and diesel fuel.The biodiesel (20 %) was blended with the reference diesel (80 %). The reference diesel and biodiesel blend values were notified to compare different timings of 1-propanol EM fumigation. 1 ms, 3 ms, and 5 ms injected fuel into the inlet manifold with varying loads. The test engine was powered by the mentioned biodiesel mixture with different timing of 1-propanol EM fumigation and reported the engine operating parameters. The test engine was subjected to additional brake power and fumigation timings. Initially, the experiments were conducted at extra engine brake power to identify the engine performance and emission characteristics, and later on, this investigation deals with the use of multi-criteria decision-making (MCDM) based Analytic Hierarchy Process (AHP) and Complex proportional assessment method (COPRAS) to identify the weights and Rank of the various tested blends. The experiment results were compared to the effects of reference diesel and biodiesel. The 5 ms 1-propanol EM fumigation produced good results in all engine parameters. The 3 ms EM fumigation produced intermediate results in all engine parameters.In comparison to 1-propanol EM fumigation timings, 5 ms produced maximum efficiency in peak load conditions and produced low carbon dioxide (CO2), nitric oxide (NO), and smoke at all load conditions.

Decision Making for the Best Hospital Evaluation Using the AHP-COPRAS Method

The assessment of the Hospital is very important in providing a rating as a measure of accreditation. Hospitals should provide the best service to visiting patients. The purpose of this study is to provide a ranking of hospitals that should be a measure of the appropriateness of a hospital as seen from a number of criteria as a true assessment. The criteria used as a barometer for the assessment consist of ten criteria, namely Administrative Services, Doctor Services, Pharmaceutical Installation Services, Cleanliness, Convenience, Security, Number of Administrative Personnel, Number of Pharmaceutical Personnel, Administrative Complaints, and Pharmacy Installation Complaints. The scoring system that will be applied uses the Analytical Hierarchy Process (AHP) method as a determinant of the weight of each criterion and the Fuzzy assessment uses the Complex Proportional Assessment (COPRAS) method. The two methods will be collaborated as a determinant in the process of giving a rating system to the ten hospitals that are included in the priority assessment. The results obtained from the ranking process of the two AHP and COPRAS methods are seen from the acquisition of the utility value produced, the largest value obtained from the utility gives the best rating. The utility value is obtained from the total assessment of a number of criteria for each hospital and the largest utility rating does not exceed one. The highest value of the utility generated by the RS10 alternative with a utility scale of 0.098 as the best value.

Rockburst Hazard Evaluation Using an Extended COPRAS Method with Interval-Valued Fuzzy Information

Rockburst is a major disaster in deep mining engineering, which can cause serious injury, death and economic losses. This study aims to solve rockburst hazard evaluation problems and determine the hazard levels of mines under uncertain circumstances. To this end, a novel multicriteria decision-making (MCDM) method was proposed in an interval-valued fuzzy context. The main contributions are three-fold. First, considering the heterogeneity of rock masses and the complexity of mining engineering, interval-valued fuzzy numbers (IVFNs) were adopted to express initial indicator information. Second, accounting for the uncertainty of indicator weights, the decision-making trial and evaluation laboratory (DEMATEL) and entropy methods were extended with IVFNs to determine fuzzy indicator weights comprehensively. Third, the complex proportional assessment (COPRAS) approach was extended with IVFNs to determine the rockburst hazard level. Finally, the proposed method was applied to evaluate rockburst hazards in the Jiaojia gold mine, and the ranking results were consistent with field status. Meanwhile, sensitivity and comparison analyses were performed to reveal the stability and effectiveness of the proposed method. The results indicated that the extended COPRAS method was reliable for rockburst hazard evaluation in deep mining engineering.

Structural design and self-locking performance verification of the snap-fit spatial self-locking energy absorption system under the impact loading

There are increasingly high performance requirements of energy-absorbing systems in aerospace, defense and military, transportation and other fields, especially in the field of emergency protection where the study of self-locking characteristics is of great significance. In this paper, an energy absorption system is designed by snap-fit thin-walled tubes, which can be edited, easy to assemble quickly and spatial omnidirectional self-locking, and the spatial self-locking characteristic of the system was verified by numerical simulation under the uniform/concentrated impact loadings. The results show that the energy-absorbing system can withstand the uniform/concentrated impact loadings in all directions in space. Furthermore, the good comprehensive performance of the loading condition in direction 3 (α = 90 deg, β = 0 deg) was verified by the quantitative analysis of the complex proportional assessment (COPRAS) method and the qualitative analysis of Radar Diagram method.

A COPRAS-based Approach to Multi-Label Feature Selection for Text Classification

In this article, we present a novel approach for text classification feature selection using a pseudo-relation matrix constructed with ridge regression. This approach involves generating a matrix that captures the relationship between features and target variables and then using that matrix to create a multi-criteria decision making (MCDM) problem. We then utilize the Complex Proportional Assessment (COPRAS) method to rank features in order of importance. To assess the performance of our proposed algorithm, we conduct tests on ten real-world text datasets and compare our results to the existing methods. Our findings indicate that the proposed approach outperforms other methods, and we provide statistical significance to support our claims. Our proposed algorithm provides a viable answer for researchers looking for efficient and effective feature selection methods for text data analysis, which can lead to a better understanding and interpretation of the underlying text.