TOPSIS Approach Research Articles

Evaluating the transformation of China's resource-based cities: An integrated sequential weight and TOPSIS approach

The transformation and development is an inevitable problem for resource-based cities (RBCs). In the process of transformation, cities in various cities, regions, resource types and development stages are having shown commonality and uniqueness. However, little work has been done on the horizontal comparison between RBCs. This paper evaluates the transformation level of 81 RBCs in China from 2006 to 2017 and investigates the transformation effect of cities in different regions, different dominant resources and different development stages. The comprehensive index system incorporating economy, society and environment is established by using the improved TOPSIS method. The results indicate that the transformation effects of most RBCs are between 0.400 and 0.800. Generally speaking, the transformation effects of four economic regions are on the rise, especially in the western region, with an increase of 17.626% from 2006 to 2015. The transformation effect of RBCs in the eastern region is the highest, while that in the northeast is the worst. Regeneration cities’ transformation effect is the best, reaching more than 0.70 in 2017. The transformation effect of growth cities is the worst, but the growth rate is the highest from 2006 to 2015. There is a rising trend of the transformation effects for oil-based cities and coal-based cities, while the transformation effects of iron-oriented cities and rare earth-oriented cities are not obvious.

An intelligent model to identify industry 4.0, IoT and circular economy adoption barriers

In the industry 4.0 idea, new cutting-edge techniques like the Internet of Things (IoT) are advocated. There is still a long way to go before IoT is widely adopted in the circular economy. The goal of this research is to identify the most significant impediments to the integration of IoT in the circular economy in the manufacturing industry. For this purpose, survey research was carried out to provide a framework for the assessment of the hurdles to IoT adoption in the circular economy. This led to a new approach that combines the SWARA and TOPSIS methodologies based on MCDM. The SWARA model is employed to compute the weights of criteria, while the TOPSIS approach is used to rank different manufacturing businesses under the identified obstacles.

Modelling the sustainable supply chain management practices in Indian industries: A business model using Fuzzy TOPSIS approach

Worldwide customers have awareness for the use of eco-friendly products, and rules and regulations imposed by government to move towards the sustainable products create pressure impacts on the indu...

The fuzzy integrated TOPSIS economy ranking (FITER) model for manufacturing technology development in China

With knowledge perspective of industrial technology, in this paper we propose fast ranking score decision making model based on Fuzzy integrated TOPSIS approach to determine economic growth rate of manufacturing industry in China. This research focuses on driving effects of China’s productive service industry on manufacturing technology innovation. The research results show that the manufacturer service industry takes a high level of information diffusion for the manufacturing industry. It transmits a large amount of diverse information through the unconstrained relationship with the manufacturing industry, thereby forming the economic network with proposed Fuzzy integrated TOPSIS economy ranking (FITER) model and improve the development level of the manufacturing industry. We evaluate the performance of proposed FITER model by comparing ranking score of different manufacturing industry with different existing decision making mode and demonstrate that proposed model represent best ranking score in comparison to existing approach. Result from data analysis motivates driving effect of production services on the technological innovation of manufacturing and sub-sectors. It is found that the innovation and technological advancement in the production industry of services takes drive the overall expansion level of the business industry, as well as make the manufacturing industry the strongest.

Modelling the sustainable supply chain management practices in Indian industries: a business model using the fuzzy TOPSIS approach

Modelling the sustainable supply chain management practices in Indian industries: a business model using the fuzzy TOPSIS approach

Evaluating the Performance of Battery Electric Vehicles using an Incorporated Decision Support Framework Based on Ranking Algorithms

The use of alternative energy sources rather than fossil fuels will be unavoidable in the nearish term due to rising levels of toxic residues that threaten natural life and human health. Furthermore, the use of fossil fuels puts subsequent generations in danger from environmental damage and climate change. Battery electric vehicles (BEVs), an environmentally friendly kind of vehicle, are important in light of transportation's significant contribution to the carbon footprint. In light of the recent fast growth of the BEV industry, it has become more important to consider all available BEV options from the perspective of the end-user. Each BEV's fundamental characteristics may be examined in order to make this evaluation. For the correct BEV buying choice, MCDM strategies are useful. As a result, eleven battery-electric vehicles (BEVs) are considered in this study. A variety of multi-criteria methodologies are used to rate these cars on the basis of their technical specifications, such as acceleration, pricing, battery life, and range. It is then used entropy weight and TOPSIS approaches to gather findings from different MCDM strategies. The entropy method is used to compute the weights of the criteria. Then the TOPSIS is used to rank the options. The 3 key considerations for BEV choosing are price, permitted load, and energy usage, with Tesla Model S emphasized as the preferred route.

Benchmarking COPRAS and TOPSIS approaches for optimization of FDM process parameters: A case of an automotive component

Benchmarking COPRAS and TOPSIS approaches for optimization of FDM process parameters: A case of an automotive component

Optimization of waste fly ash powder filled glass fiber reinforced epoxy composite by hybrid AHP-TOPSIS approach

Abstract The current research work aims to optimize the waste fly ash powder filled glass fiber reinforced epoxy composites (i.e. EGF 0; EGF 5; EGF;10; EGF 15) by using hybrid AHP-TOPSIS technique. For determining the ranking order of composite formulations, following characteristics like: physical, mechanical, tribological and thermo-mechanical have been selected for performance determining criteria (PDC). As per AHP the order of PDCs is: PDC-1 (Tensile Strength) > PDC-5 > (Impact Strength) > PDC-2 (Tensile Modulus) ∼ PDC-3 (Flexural Strength) ∼ PDC-4 (Flexural Modulus) > PDC-8 (Tan δ) ∼ PDC-11 (Abrasive Wear Rate) ∼ PDC-12 (Cost) > PDC-6 (Hardness) ∼ PDC-7 (Storage Modulus) ∼ PDC-9 (Void) > PDC-10 (Experimental Density) respectively. The verification of consistency is also observed and the maximum Eigen value (λmax) ∼ 12; Consistency index (CI) = 0.004 and Consistency Ratio (CR) = 0.002.As per TOPSIS approach the ranking order of the selected compositions is: EGF-10 > EGF-15 > EGF-5 > EGF-0 respectively.

Evaluating ICT Usage in Enterprises in Europe: Topsis Approach

Abstract The main objective of the paper is to evaluate ICT usage in enterprises in 31 European countries. For that purpose, ICT usage in enterprises index (ICTEI) was developed using the TOPSIS approach based on the entropy method. Subsequently, having used the cluster analysis, countries were classified into clusters according to the observed indicators of ICT usage. Results show that Finland, Denmark, Norway, Sweden and Ireland are the top 5 countries when the advanced ICTs are prioritized. Based on the k-means clustering, Finland is a leader in a cluster of a very high ICT usage in enterprises and it is followed by Denmark, Norway, and Sweden. The cluster of high ICT usage in enterprises includes Ireland, Netherlands, Slovenia, Spain, and United Kingdom. Finally, the countries characterized by moderate and modest ICT usage are positioned in the remaining two clusters. The results of this research will facilitate the perception of a country’s position in relation to others, but will also signal the need to take measures to strengthen the ICT capacity of the business sector in the countries with a low value of ICTEI.

Financial Performance Analysis of Banks with Topsis and Fuzzy Topsis Approaches

Banks are one of the key components in the world economy's financial activities. With the increasing competitive environment, banks need to use their resources effectively. Effective and efficient operation of banks is one of the important issues of money and financial markets. Effective operation of banks that are at the center of the economy, and measuring and evaluating their performances both determine their positions in the sector and have strategic importance on process management of the country’s economy. Determining which criteria and weights will be determined for performance is very important in the multi-criteria decision making process. Fuzzy techniques have more sensitivity in such evaluations. Fuzzy approaches are preferred as the risk, uncertainty and competition continue to increase in the banking sector. In this study, the criteria that affect the financial performance of banks are determined. Based on relevant criteria, the first seven banks were ranked in total assets according to reports received from The Banks Association of Turkey for 2014-2018 financial year and a performance evaluation was done by using the TOPSIS and Fuzzy TOPSIS methods.

Optimization and effect of load, sliding velocity, and time on wear behavior of AA8011- 8 wt.% fly-ash composites

This research work was undertaken to study the effect of dry sliding wear process parameters such as load, time, and sliding velocity on the wear rate and coefficient of friction of AA8011 with 8 wt.% fly-ash composites. The response surface methodology was used to determine the most important criteria to maximize the wear rate and minimize the coefficient of friction. The experimental procedure was designed based on second-order rotatable central composite design. The optimization studies were carried out on dry sliding wear process parameter with multi-response characteristics, including the wear rate, coefficient of friction, based on multi-criteria decision-making using the TOPSIS approach. Sensitivity analysis was used to identify the important criteria and classify them by their order of importance in model validation. A confirmation test was carried out to validate the results, and the obtained optimal parameter levels were found to be very close to an ideal solution.

Large-scale multiple criteria decision-making with missing values: project selection through TOPSIS-OPA

Nowadays, with the development of information management infrastructures in organizations and the improvement of the data storage process, managers are looking for appropriate decision-making methods based on large volumes of data. Therefore, it is crucial to choose the right approach to make the right decisions based on the volume of available data. The present study seeks to provide a comprehensive framework for the decision-making process using big data, even when it is incomplete. The framework of multiple criteria decision making (MCDM) consists of criteria and alternatives, whereas in real-world cases, decision-makers may face several criteria and alternatives. In this study, the Principal Component Analysis (PCA) approach was selected for the criteria clustering. Later, the K-means algorithm is used to cluster the alternatives, which estimates the optimal number of clusters using the Elbow method. The Fuzzy TOPSIS (TOPSIS-F) and Ordinal Priority Approach (OPA) have been used to rank clusters. Ultimately, the best alternative in the top cluster has been identified with the aid of the OPA, which has a unique function to solve MCDM problems with incomplete data. For evaluating the performance of the proposed approach, first, a pilot testing has been executed on a real-world case, and then a practical study was conducted at a refinery equipment manufacturing company with a project-oriented organizational structure. The approach is flexible, interactive, intelligent, and integrative, and significantly reduces the time and computation costs for the decision-makers. The results confirmed the soundness of the proposed approach, which can be used by managers of different companies with confidence.

Developing the structural model based on analyzing the relationship between the barriers of green supply chain management using TOPSIS approach

Day-to-day, growing environmental impact on the industries has forced them to go for sustainable development in the industry. Further, the growing awareness among consumers regarding environmental concern dictates the path for the manufacturing context to think about greening in all the processes. In this regard, Green Supply Chain is one of the best options before the industries. GSCM is not only converting the industrial operations as green operations but also providing the safeguard against the hazardous objects associated with the industries. Though comparing with traditional SCM, the implementation of the GSCM approach in the manufacturing sector seems to be a complex one, yet it can be implemented. In the Indian context, it is revealed that there is a slow progression in the implementation of GSCM. The present study discusses the barriers responsible for the slow implementation of GSCM. Further, an attempt has been made to validate and ranking to these barriers with the help of the TOPSIS method. The study concludes that government policies and regulations are the foremost impacted barrier that causes the slow implementation of GSCM in the Indian context.

DEVELOPMENT OF A NEW HYBRID MULTI CRITERIA DECISION-MAKING METHOD FOR A CAR SELECTION SCENARIO

Increasing competition in the automobile industry has led to a vast variety of choices when buying a car thus making car selection a tedious task. The objective of this research is to develop a new hybrid multi-criteria decision-making technique, with accuracy greater than that of the already existing methods, in order to help the people in decision-making while buying a car. Hence, considering a broader spectrum, this study aims at easing the process of multi-criteria decision-making problems in different fields. To achieve the objective, seven different alternatives were evaluated with respect to the enlisted evaluation criteria, which were selected after analyzing the secondary data obtained from Pak wheels based on style, fuel economy, price, comfort and performance. These criteria were then analyzed using the proposed Full Consistency Fuzzy TOPSIS method. As the name tells, this method is a unique combination of two techniques. The Full Consistency method is used to calculate the weights of the criteria while the Fuzzy TOPSIS approach is applied to rank the alternatives according to their scores in the selected criteria. The outcomes demonstrate an increase in the consistency ratio of the weight coefficients due to which the ranking of the alternatives by the FCF-TOPSIS is more accurate than the TOPSIS and the Analytical Hierarchy Process. The novelty of the method lies in the fact that this combination has not been used for an alternative selection scenario before. In addition to this, it can be used in various industries where a choice between the available alternatives arises based on a set of evaluation criteria.

Novel MCGDM with q-rung orthopair fuzzy soft sets and TOPSIS approach under q-Rung orthopair fuzzy soft topology

In this article, we study some concepts related to q-rung orthopair fuzzy soft sets (q-ROFS sets), together with their algebraic structure. We present operations on q-ROFSSs and their specific properties and elaborate them with real-life examples and tabular representations to develop influx of linguistic variables based on q-rung orthopair fuzzy soft (q-ROFS) information. We present an application of q-ROFS sets to multi-criteria group decision-making (MCGDM) process related to the university choice, accompanied by algorithm and flowchart. We develop q-ROFS TOPSIS method and q-ROFS VIKOR method as extensions of TOPSIS (a technique for ordering preference through the ideal solution) and VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje), respectively. Finally, we tackle a problem of construction business utilizing q-ROFS TOPSIS and q-ROFS VIKOR methods.

Multi-response optimization of AA 8011 and 12 wt.-% fly ash composites

Abstract The present research work is focused on the production of aluminum alloy 8011 with 12 wt.-% fly ash composite by using the stir casting method. A three-level central composite design experiment is developed using response surface methodology (RSM) with various parameters. Load, time and sliding velocity are varied in the range of (5-15 N), (5-15 min) and (1.5-4.5 m × s-1), respectively. Dry sliding wear tests are performed as per the experimental design using a pin-on-disc at room temperature. This paper describes how optimization studies were carried out on a dry sliding wear process with multi-response characteristics based on MCDM using the TOPSIS approach. The process parameters, load, time and sliding velocity are optimized with multi-response characteristics, including the wear rate (WR), and the coefficient of friction (COF). A sensitivity analysis is also carried out and compared with the relative impact of input parameters on wear behavior in order to verify the measurement errors on the values of the uncertainty in estimated parameters. The experimental results indicate that the multi-response characteristics of aluminum alloy 8011 with 12 wt.-% fly ash composite used during the wear behavior process can be enhanced through the TOPSIS method.

Balanced scorecard-based analysis of customer expectations for cosmetology services: a hybrid decision modeling approach

The goal of this study is to analyze and characterize customer expectations in the cosmetics sector. Within this framework, first, the extant literature is reviewed, and 12 most prominent performance measurement criteria are identified. Then, these criteria are organized along the four different balanced scorecard dimensions. By employing an Interval Type-2 Fuzzy DEMATEL methodology, the weighted importance of these dimensions and criteria are identified. Additionally, with the Interval Type-2 Fuzzy TOPSIS approach, 13 leading cosmetic service providers in Ukraine are ranked based on their relative scores. The findings of the study indicate that consumer is the most significant dimension while learning and growth seem to have the least importance. Similarly, it is also concluded that all consumer-focused criteria (i.e. diversification of services, feedback on the product and services, and customer loyalty) have the highest priorities in the complete criterion set.

Risk assessment of hydrogen generation unit considering dependencies using integrated DEMATEL and TOPSIS approach

Hydrogen generation is with highly operational risk, and the catastrophic consequence may be caused as hydrogen is easily inflammable and explosive. It is of great importance to perform an effective risk assessment to ensure the operational safety of hydrogen generation unit. This paper presents a novel framework comprising of fuzzy DEMATEL implemented with TOPSIS to assess the comprehensive risk of hydrogen generation unit. This methodology is capable of capturing the interdependencies among different hazards, and prioritize the hazards in the decision-making process. An index-based risk assessment system is built by identifying hazards related to hydrogen generation. Subsequently, fuzzy DEMATEL is used to extract the interrelationships among risk indices and determine their weights, and TOPSIS model is utilized to prioritize hazards and calculate their risk values. Eventually, the risk of hydrogen generation unit is assessed by integrating the initial risk values with the weights of evaluation indices. The safety strategies based on assessment outcomes are developed to reduce the risk of hydrogen generation. A case study is used to test the practicability of the methodology, and it is observed that it can be a useful tool to risk assessment and management of hydrogen generation unit.

Application of TOPSIS method in selection of design attributes of decision support system for fertilizer recommendation

The selection of the most suitable design attributes out of available alternatives is usually remains a tedious and time-consuming task for designers. Due to complex design specifications and availability of multiple design alternatives of agricultural decision support systems for fertilizer prescriptions, the selection of design attributes is generally seen to be a multi-criterion decision-making problem. From the designer’s perspective, it is very important to build a decision model that helps in the identification and selection of the most suitable design attributes by using some standard, faster, and more objective methodology. To meet this objective, this paper presents a decision model to select the design attributes for the futuristic intelligent fertilizer recommendation system (IFRS) using the TOPSIS approach. The model first identifies the various design aspects and criteria as inputs for the TOPSIS method through a detailed study of existing DSS cum FRS. By using the identified criteria, a few of the state of art selected FRS are ranked and prioritize in order of preference by applying the TOPSIS approach. The ensemble of design attributes of the top-ranked FRS such as data inputs development technologies and support delivery methods are chosen as design specifications for futuristic IFRS. The author believes that the presented decision model will help the designers in the selection of design attributes and proposal of futuristic IFRS design.

Evaluating critical barriers and pathways to implementation of e-waste formalization management systems in Ghana: a hybrid BWM and fuzzy TOPSIS approach

The majority of developing countries are facing enormous challenges in implementing sustainable waste electrical and electronic equipment (e-waste) management systems. Informal e-waste management practices in Ghana have become a critical challenge to the government and the various stakeholders owing to its environmental and health impacts. However, the effort to implement e-waste formalization management practices has been threatened with many barriers. This study aims to identify and evaluate barriers and pathways to the implementation of e-waste formalization management systems in Ghana. A three-phase methodology consisting of the Delphi method, the hybrid best-worst method and the fuzzy TOPSIS technique is employed. The first phase involves extensive literature review and the use of the Delphi method to identify barriers, pathways, and data collection for e-waste formalization. In the second phase, the best-worst method was employed to analyze the relative weight and ranking of the barriers. The third phase involves the application of fuzzy TOPSIS to rank and prioritize pathways to e-waste formalization systems. Fuzzy logic was applied to handle the subjectivity of decision-makers' preferences. A sensitivity analysis was carried out to check the robustness of the framework and address any effect of bias. The outcome of the study indicates that economic and financial limitations are the most significant barriers to e-waste formalization. "Setting up resourced environmental government agencies for effective monitoring and auditing at the regional levels for appropriate e-waste management practices" is the most prominent pathway. The present study can potentially inform policy makers to develop systematic and strategic policies for the implementation of e-waste formalization management systems.