Three Decades of Fuzzy AHP: A Bibliometric Analysis

[EN] For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field¿s agenda to advise the editors of high-impact journals on gaps and new research trends.Castello-Sirvent, F.; Meneses-Eraso, C.; Alonso-Gómez, J.; Peris-Ortiz, M. (2022). Three Decades of Fuzzy AHP: A Bibliometric Analysis. Axioms. 11(10):1-34. https://doi.org/10.3390/axioms11100525134111

İMALAT İSÇİLERİNİN SEÇİM KRİTERLERİNİN BULANIK AHS YÖNTEMİ İLE ANALİZİ

An analytical way to reach the best decision is more preferable in many business platforms. When variables are quantitative and number of criteria is not high, then one can use several analysis tools and make his/her decision and solve the problem. However, many times beside the measurable variables, there exist qualitative variables for decision making problems, or people are supposed to prefer the best among the many choices. Even if only linguistic evaluations may be available for such problems, an analytical way to find the solution systematically to make a successful decision is needed. Fuzzy Analytical Hierarchy Process (Fuzzy AHP) is one of the best ways for deciding among the complex criteria structure in different levels. Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision makers is considered. In this paper, the criteria set and their importance for the selection of manufacturing employee in a firm producing shoe machines are analyzed. Finally a systematic solution and decision support are provided for management. Birçok is ortamında analitik yöntemler, en iyi kararı vermek adına daha çok tercih görmektedir. Sayısal olarak ölçülebilen degiskenlerin ve kriterlerin varlıgında kullanılabilecek birçok analiz ve problem çözme teknigi bulunabilirken, kalitatif degiskenlerle seçim ya da karar verme zorunlulugu oldugunda farklı yaklasımlara gerek duyulmaktadır. Böyle bir durumda, öznel ve sözel degerlendirmeler yapma zorunlugu dogmakla birlikte, sistematik ve analitik bir yol izlemek basarılı karar vermek açısından kaçınılmazdır. Bu kosularda özellikle karar verme ortamı bulanık veriler içeriyorsa, en çok tercih edilen tekniklerden biri de Bulanık Analitik Hiyerarsi Süreci (Bulanık AHS)dir. Karmasık kriter set ve çoklu düzey yapısında seçenekler içerisinde en iyi seçimi yapma konusunda basarılı kararlar alınmasında sık kullanıma sahiptir. Bulanık AHS karar vericilerin yaptıkları yorum ve degerlendirmelerde belli bir bulanıklık oldugu düsünüldügünde ortaya çıkan ve AHS'nin bir uzantısı olarak gelistirilen sentetik bir yaklasımdır. Bu çalısmada, ayakkabı makinalar üreten bir firma için imalatta çalısacak isçilerin seçiminde hangi kriterlerin gözetildigi ve bu kriterlerin hangi agırlıklarla kararda etkili oldugu bulanık AHS yöntemi ile analiz edilmis, firma yetkilerine sistematik bir çözüm ve karar destegi saglanmıstır

CAD Software Evaluation for Product Design to Exchange Data in a Supply Chain Network

The sharing information in a supply chain environment, especially CAD models and drawings are so important companies. So, the selection of the most satisfying computer-aided design (CAD) software which enables to exchange data through supply chain network has been major issues for companies in a supply chain. The selection process of CAD software among the raising number of alternatives in the market has been very vital and critical issue for companies that aim to make their design and engineering related activities automated towards computer integrated manufacturing (CIM) environment. Therefore, most companies have used various methods to successfully carry out this difficult and time-consuming process. Of these methods, Analytic Hierarchy Process (AHP) has been widely used for Multiple Criteria Decision Making (MCDM) problems in both academic researches and practices. But, in some cases, due to the vagueness and uncertainty on judgments of the decision-maker(s), the crisp pair wise comparison in the conventional AHP seems to be insufficient and imprecise to capture the right judgments of decision-maker(s). Therefore, a fuzzy logic is introduced in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP, called as fuzzy AHP. In this paper, a fuzzy AHP-based approach is proposed to evaluate a set of CAD software alternatives in the market to reach the best satisfying one based on the needs of company

Unlocking the Potential of Blockchain Through Multi-Criteria Decision Making in Platform Selection

Purpose: The purpose of this paper is to introduce a methodology that can help organizations choose the best Blockchain platform for their specific business case. With numerous options available, it's important to carefully consider the capabilities of a Blockchain before selecting it. This methodology is intended to provide a structured approach to aid in the decision-making process, taking into account the various characteristics of Blockchain that are needed.   Theoretical Framework: The theoretical framework for this paper is based on Multi Criteria Decision Making (MCDM) and ISO/IEC 25010. MCDM is a decision-making technique that considers multiple criteria when making a choice, which is useful for selecting the best Blockchain platform. ISO/IEC 25010 is a standard that provides a framework for evaluating software quality characteristics, which is relevant for evaluating the quality of the Blockchain platform.   Design/Methodology/Approach: The methodology presented in this paper involves a structured approach to selecting the best Blockchain platform for a specific business case. The approach is based on a combination of MCDM and ISO/IEC 25010, and involves several steps. First, the relevant criteria for selecting the Blockchain platform are identified. Next, a weighting system is developed to determine the importance of each criterion. Then, each Blockchain platform is evaluated based on the criteria and weights, and a score is assigned. Finally, the scores are aggregated to determine the best Blockchain platform for the specific business case.   Findings: The main finding of this paper is the methodology for selecting the best Blockchain platform for a specific business case. This methodology can aid organizations in making an informed decision when choosing a Blockchain platform, taking into account the various characteristics of Blockchain that are needed. The paper also highlights the importance of careful consideration when selecting a Blockchain platform, as the wrong choice could have negative consequences.   Research, Practical & Social Implications: The research implications of this paper are significant, as it provides a structured approach for selecting the best Blockchain platform for a specific business case. This methodology can be used across industries and could have a significant impact on the adoption of Blockchain technology. From a practical perspective, this methodology can aid organizations in making informed decisions when selecting a Blockchain platform, which can save time and resources. From a social perspective, the adoption of Blockchain technology has the potential to revolutionize business operations and improve transparency and accountability.   Originality/Value: The originality of this paper lies in the development of a methodology for selecting the best Blockchain platform for a specific business case. This methodology is based on a combination of MCDM and ISO/IEC 25010 and is not specific to any one industry. The value of this paper is in providing a structured approach to aid organizations in making an informed decision when selecting a Blockchain platform, taking into account the various characteristics of Blockchain that are needed

A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

Intelligent Multi-Attribute Decision Making Applications: Decision Support Systems for Performance Measurement, Evaluation and Benchmarking

Efficiency has been and continues to be an important attribute of competitive business environments where limited resources exist. Owing to growing complexity of organizations and more broadly, to global economic growth, efficiency considerations are expected to remain a top priority for organizations. Continuous performance evaluations play a significant role in sustaining efficient and effective business processes. Consequently, the literature offers a wide range of performance evaluation methodologies to assess the operational efficiency of various industries. Majority of these models focus solely on quantitative criteria omitting qualitative data. However, a thorough performance measurement and benchmarking require consideration of all available information since accurately describing and defining complex systems require utilization of both data types. Most evaluation models also function under the unrealistic assumption of evaluation criteria being dependent on one another. Furthermore, majority of these methodologies tend to utilize discrete and contemporary information eliminating historical performance data from the model environment. These shortcomings hinder the reliability of evaluation outcomes leading to inadequate performance evaluations for many businesses. This problem gains more significance for business where performance evaluations are tied in to important decisions relating to business expansion, investment, promotion and compensation. The primary purpose of this research is to present a thorough, equitable and accurate evaluation framework for operations management while filling the existing gaps in the literature. Service industry offers a more suitable platform for this study since the industry tend to accommodate both qualitative and quantitative performance evaluation factors relatively with more ease compared to manufacturing due to the intensity of customer (consumer) interaction. Accordingly, a U.S. based food franchise company is utilized for data acquisition and as a case study to demonstrate the applications of the proposed models. Compatible with their multiple criteria nature, performance measurement, evaluation and benchmarking systems require heavy utilization of Multi-Attribute Decision Making (MADM) approaches which constitute the core of this research. In order to be able to accommodate the vagueness in decision making, fuzzy values are also utilized in all proposed models. In the first phase of the study, the main and sub-criteria in the evaluation are considered independently in a hierarchical order and contemporary data is utilized in a holistic approach combining three different multi-criteria decision making methods. The cross-efficiency approach is also introduced in this phase. Building on this approach, the second phase considered the influence of the main and sub-criteria over one another. That is, in the proposed models, the main and sub-criteria form a network with dependencies rather than having a hierarchical relationship. The decision making model is built to extract the influential weights for the evaluation criteria. Furthermore, Group Decision Making (GDM) is introduced to integrate different perspectives and preferences of multiple decision makers who are responsible for different functions in the organization with varying levels of impact on decisions. Finally, an artificial intelligence method is applied to utilize the historical data and to obtain the final performance ranking. Owing to large volumes of data emanating from digital sources, current literature offers a variety of artificial intelligence and machine learning methods for big data analytics applications. Comparing the results generated by the ANNs, three additional well-established methods, viz., Adaptive Neuro Fuzzy Inference System (ANFIS), Least Squares Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), are also employed for the same problem. In order to test the prediction capability of these methods, the most influencing criteria are obtained from the data set via Pearson Correlation Analysis and grey relational analysis. Subsequently, the corresponding parameters in each method are optimized via Particle Swarm Optimization to improve the prediction accuracy. The accuracy of artificial intelligence and machine learning methods are heavily reliant on large volumes of data. Despite the fact that several businesses, especially business that utilize social media data or on-line real-time operational data, there are organizations which lack adequate amount of data required for their performance evaluations simply due to the nature of their business. Grey Modeling (GM) technique addresses this issue and provides higher forecasting accuracy in presence of uncertain and limited data. With this motivation, a traditional multi-variate grey model is applied to predict the performance scores. Improved grey models are also applied to compare the results. Finally, the integration of the fractional order accumulation along with the background value coefficient optimization are proposed to improve accuracy

An Integration of Rank Order Centroid, Modified Analytical Hierarchy Process and 0-1 Integer Programming in Solving A Facility Location Problem

Hadhramout province is the major producer of dates in The Republic of Yemen. Despite producing substantial quantity and quality of dates, the business losses are still high. The situation worsens with the widespread of the black market activities. Recently, the Yemeni government has issued an agreement stating the importance of building a date palm packaging factory as a resolution to the problems. Hence, this study aims to identify the best location for a date palm packaging factory among the seven districts which produce most of the date palm supplies in Hadhramout. The selection was based on eleven criteria identified by several representatives from the farmers and the local councils. These criteria were market growth, proximity to the markets, proximity to the raw materials, labor, labor climate, suppliers, community, transportation cost, environmental factors, production cost, and factory set up cost. The level of importance and the respective weight of each criterion were calculated using two different approaches, namely, Analytic Hierarchy Process (AHP) and Rank Order Centroid (ROC). In applying AHP, a slight modification was made in the pairwise comparison exercises that eliminated the inconsistency problem faced by the standard AHP pairwise comparison procedure. Likewise, in applying ROC, a normalization technique was proposed to tackle the problem of assigning weights to criteria having the same priority level, which was neither clarified nor available in the standard ROC. Both proposed techniques revealed that suppliers were the most important criterion, while community was regarded to be the least important criterion in deciding the final location for the date palm factory. Combining the criteria weights together with several hard and soft constraints that were required to be satisfied by the location, the final location was determined using three different mathematical models, namely, the ROC combined with 0-1 integer programming model, the AHP combined with 0-1 integer programming model, and the mean of ROC and AHP combined with 0-1 integer programming model. The three models produced the same result; Doean was the best location. The result of this study, if implemented, would hopefully help the Yemeni government in their effort to improve the production as well as the management of the date palm tree in Hadhramout

Intelligent Mobility in Smart Cities

Smart Cities seek to optimize their systems by increasing integration through approaches such as increased interoperability, seamless system integration, and automation. Thus, they have the potential to deliver substantial efficiency gains and eliminate redundancy. To add to the complexity of the problem, the integration of systems for efficiency gains may compromise the resilience of an urban system. This all needs to be taken into consideration when thinking about Smart Cities. The transportation field must also apply the principles and concepts mentioned above. This cannot be understood without considering its links and effects on the other components of an urban system. New technologies allow for new means of travel to be built, and new business models allow for existing ones to be utilized. This Special Issue puts together papers with different focuses, but all of them tackle the topic of smart mobility