Intuitionistic Fuzzy Analytic Hierarchy Process Research Articles

Risk assessment of fire safety in large-scale commercial and high-rise buildings based on intuitionistic fuzzy and social graph

Fire risk assessment is a useful method to identify potential fire risks and improve safety management, especially for those large-scale commercial and high-rise buildings. However, after the establishment of the fire risk indexing system, the weight assignment in the existing assessment methods is not scientific and objective enough to synthesize the opinions of multiple experts with different knowledge backgrounds and working experience. To solve this problem, a novel fire risk assessment for large-scale commercial and high-rise buildings is proposed with intuitionistic fuzzy and social graph. First, based on the national standards of fire safety management, the monthly maintenance and the annual fire assessment reports, the indexing system is established. Then, a scientific and objective weight assignment method called Social Graph based Intuitionistic Fuzzy Analytic Hierarchy Process (SGIFAHP) is proposed such that (1) by utilizing the intuitionistic fuzzy and social graph, it can synthesize the positive, negative and hesitant opinions from multiple experts by considering the importance of experts; (2) a novel mechanism is designed to automatically check and repair the consistency of the opinions of each expert when the expert compares the importance of risk factors. To validate the performance of the proposed method, eleven buildings are selected and their fire safety data are collected. A comparison analysis is carried out with the existing methods to compare the assigned weights. The comparison and score validation conclude that the proposed method can assign more reasonable, scientific and objective weights than the existing methods while the scores are comprehensive and strongly interpretable. In the end, a guide is offered to help safety owners and inspectors improve fire safety with the proposed method.

Bridge Construction Risk Assessment Based on Variable Weight Theory and Cloud Model

In order to effectively prevent the occurrence of risky accidents during bridge construction, this study proposes a bridge construction risk assessment method based on variable weight theory and the cloud model theory. Firstly, the fishbone diagram was used to identify risk factors in constructing a bridge construction risk index system. Secondly, according to the cloud model theory, the comment cloud model of each risk index was established by using the forward cloud generator. Finally, the risk factor weights were quantified according to the intuitionistic fuzzy analytic hierarchy process (IFAHP). Combined with the variable weight theory, a zoning variable weight function was constructed and the weights were reallocated. Through the mutual aggregation of the comment cloud model and weights, the risk level of construction bridges was obtained. The method takes full account of the fuzziness and randomness existing in the evaluation process, optimizes the distribution of weight values of indicators, and uses Delphi iteration to effectively eliminate the subjective defects of individuals. A construction bridge in Changchun was used as an example for risk assessment, and the advance of the method was well verified. The results demonstrate that the method is highly feasible and effective after accuracy verification and sensitivity analysis.

Proportional intuitionistic fuzzy AHP method: Wind turbine selection application

The direct assignment of decimal numbers for membership and non-membership degrees of an element in intuitionistic fuzzy sets is not practical. The problem is that the expert cannot assign the same values to the degrees of membership, non-membership and hesitancy in decimal numbers for the same proposition in every attempt. Rather than the former, the assignment of proportional relationships between membership and non-membership degrees is more appropriate. We propose proportion-based models for intuitionistic fuzzy sets that include arithmetic and aggregation operators. Proportional intuitionistic fuzzy (PIF) sets require only the proportion relations between an intuitionistic fuzzy set’s parameters. These models will make it easier to define intuitionistic fuzzy sets with more accurate data that better represents expert judgments. We transform AHP method, one of the traditional multi-criteria decision making methods, to PIF AHP using PIF sets. We compare the proposed PIF AHP method by interval-valued intuitionistic fuzzy AHP method existing in the literature. A wind turbine selection problem is handled to show the validity of the proposed PIF AHP method.

A portfolio selection using the intuitionistic fuzzy analytic hierarchy process: A case study of the Tehran Stock Exchange

<abstract><p>In today's economic world, due to the growth of the capital market, the importance for people to invest has increased. The most important concern for investors is choosing the best portfolio for investment. For complex decisions in which the decision maker is ambiguous, such as portfolio selection, using the multi-criteria decision making (MCDM) technique to prioritize options and decide on the optimal choice is the best solution. In this research, a generalization of this method utilizing the intuitionistic fuzzy analytic hierarchy process (IFAHP) was discussed. Considering the importance of this topic in today's economy, the purpose of this research was to describe and apply the new integrated technique of IFAHP for ranking the portfolio of companies admitted to the Tehran Stock Exchange. For this purpose, using the statistics published by the Tehran Stock Exchange, six companies including Jabra Ben Hayyan, Kaghazsazi Kaveh, Laabiran, Daro Luqman, Pashme Shishe Iran, and Bourse Kala Iran were examined. These companies were the best options for investment according to the charts and indices of the stock exchange at the time of our research. Finally, using the technique mentioned above, we described the evaluation and ranking of portfolios for confident and efficient decision -making.</p></abstract>

A novel approach integrating IF-AHP, IF-DEMATEL and CoCoSo methods for sustainability management in food digital manufacturing supply chain systems

PurposeFood manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply inefficiencies have been reported to compromise food safety in different regions. Sustainable supplier management and digitalization practices have become cornerstone activities in addressing these shortcomings. Therefore, this paper proposes an integrated method for sustainability management in digital manufacturing supply chain systems (DMSCS) from the food industry.Design/methodology/approachThe Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) was used to weigh the criteria and subcriteria under uncertainty. Second, the Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) was applied to determine the main DMSCS sustainability drivers whilst incorporating the expert's hesitancy. Finally, the Combined Compromise Solution (CoCoSo) was implemented to pinpoint the weaknesses hindering DMSCS sustainability. A case study from the pork supply chain was presented to validate this method.FindingsThe most important criterion for DMSCS sustainability management is “location” while “manufacturing capacity” is the most significant dispatcher.Originality/valueThis paper presents a novel approach integrating IF-AHP, IF-DEMATEL, and CoCoSo methods for sustainability management of DMSCS pillaring the food industry.

Sustainable stationary hydrogen storage application selection with interval-valued intuitionistic fuzzy AHP

The transition to a hydrogen-based economy necessitates a comprehensive evaluation of different hydrogen storage options, considering their sustainability performance. This study innovatively applies the Interval-Valued Intuitionistic Fuzzy Analytic Hierarchy Process (IVIF-AHP) to evaluate and compare four hydrogen storage options: Compressed Hydrogen Gas (CHG), Cryogenic Liquid Hydrogen (CLH), Metal Hydride (MH), and Underground Hydrogen (UH). The evaluation criteria are derived from four dimensions of sustainability: economic, environmental, social, and technical performance, each further decomposed into sub-criteria. The study's novelty lies in using a novel intuitionistic fuzzy AHP, offering a more nuanced and robust understanding of the trade-offs between the various options and effectively capturing the vagueness and subjectivity inherent in human decision-making. Through this methodology, CHG emerged as the most promising option with a preference score of 0.487, closely followed by UH with a score of 0.453. The lowest preference score was accorded to MH, with a score of 0.301. These quantitative insights underscore the relative sustainability performance of each technology under the defined criteria. The findings contribute to the growing body of literature on sustainable hydrogen storage, providing policymakers and practitioners with a multicriteria decision-making tool that captures the complexity of sustainability considerations. This study underlines the critical role of holistic, multicriteria evaluations in advancing sustainable hydrogen storage. It encourages further exploration and validation of its approach in different contexts and with updated technological advancements.

An intuitionistic fuzzy based hybrid decision-making approach to determine the priority value of indicators and its application to solar energy feasibility analysis

Solar plant feasibility involves assessing its practicality and viability for successful development and operation. It involves evaluating various factors to determine whether the project is technically, economically, and environmentally feasible. Feasibility analysis considers solar resource availability, site selection, technology options, financial viability, grid integration, regulatory compliance, and potential risks. By conducting a comprehensive feasibility study, developers can determine if a solar plant is a feasible and sustainable solution to generating renewable energy at a specific location. An intelligent mitigation measure is proposed in this paper to control the trade-off by using certain indicators that have the greatest influence on the feasibility of a solar power plant. This study proposes a novel subjective weighting technique known as the Intuitionistic Fuzzy Consistency Method (IF-FUCOM) to achieve the highest degree of precision when considering fuzziness. Intuitionistic Fuzzy Set (IFS) handles imprecise information flexibly. Therefore, the IFS has gained interest from experts and is being applied to various fields, especially decision-making. Furthermore, the study identifies the local weights of alternatives using the Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP). This study proposed a hybrid method, IF-FUCOM-AHP, for determining the global weight. Its robustness and effectiveness are demonstrated by comparing the proposed fuzzy model with three existing hybrid methods and developing a novel index for evaluating solar project feasibility and location. Finally, a scenario analysis and sensitivity analysis of different options are conducted for different solar power plants. The benefit of the suggested approach lies in its IFS utilization. This method resolves the issue by delineating the non-membership and membership degrees of elements within a fuzzy set, while also providing a means to articulate a particular level of uncertainty.

Risk assessment for pharmaceutical industry in uncertain environment: An integrated multi-criteria decision-making approach

The pharmaceutical industry is the backbone of the healthcare system for any country. However, this industry faces various risks, which hamper its efficient working in providing life-saving medicines/services to the people. In this context, the purpose of the study is to improve the resilience and performance of the pharmaceutical industry (PI) with the identification, and assessment of supply chain (SC) risks. A case illustration has also been presented in the Indian context. The study utilizes an extensive literature survey and the Delphi method for identifying, finalizing, and classifying the risks into seven categories. The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) has been used to analyze and prioritize the risks to determine their criticality. The results show that the three most important risks are financial, supplier, and demand/customer/market. Within these risks, the three most critical sub-risks are found to be loss of customers, raw material (RM) issues, and bad reputation of the company, respectively. The study provides managers with an extensive list of PI risks for their consideration. The results also present the critical risks which need to be mitigated for enhanced performance and resilience of the industry. The study also emphasizes the importance of interconnection between various SC partners for better risk management.

Multidimensional Evaluation of Consumers’ Shopping Risks under Live-Streaming Commerce

As a new e-commerce model, live-streaming commerce enhances consumers’ shopping experiences by providing deeply involved online interaction. However, in live-streaming commerce, consumers are also faced with many shopping risks, such as fake products, poor after-sales service, etc. Therefore, we propose an analysis framework to evaluate consumers’ shopping risks on live-streaming commerce platforms. In our framework, we first construct a multidimensional consumer shopping risk evaluation index system by considering different stakeholders involved in live-streaming commerce. Then, we assess consumer shopping risks based on an intuitionistic fuzzy analytic hierarchy process and cloud model. Our framework is applied to evaluate consumers’ shopping risks on four typical live streaming commerce platforms in China, i.e., Taobao, Douyin, Kuaishou, and JD.com. Our research results provide decision support for different parties involved in live-streaming commerce and thus promote the sustainable development of the live-streaming commerce industry.

Prioritisation of operations during emergency shutdown of a crude distillation unit by interval-valued intuitionistic fuzzy analytic hierarchy process

A very reliable control system for offering a safety layer in emergency scenarios is an emergency shutdown system, or ESD system. It aids in preventing crises from having disastrous effects on the economy, the environment or business operations. In any plant, emergency shutdown systems reduce the risk of harm to the working population, the environment or equipment damage by guarding against leaks, hydrocarbon escapes, fire outbreaks and explosions. The ESD system halts process activity in an emergency, ensures that the hazard is isolated and does not worsen. It is essential that there is a clearly defined emergency procedure in place when a facility needs to be shut down in an emergency. When preparing an emergency procedure for use in an emergency, it is crucial to prioritise the operations. The factory uses an Interval-valued Intuitionistic Fuzzy Analytical Hierarchy Process (IVIFAHP) to prioritise activities in emergency situations. It is possible to design emergency shutdown systems using the aforementioned order of operations. It is possible to properly set up safety measures using the multi-criteria decision-making approach (MCDM). The Analytical Hierarchy Process (AHP) compares variables without taking measurement scales or units into consideration, which is a distinct benefit. The AHP’s handling of ambiguity, uncertainty and imprecise data is improved by the IVIFAHP.

A novel interval valued circular intuitionistic fuzzy AHP methodology: Application in digital transformation project selection

Since its first introduction, ordinary fuzzy sets have been extended to new types of fuzzy sets as a tool of artificial intelligence techniques. One of the recently introduced fuzzy sets, “Circular Intuitionistic Fuzzy (CIF)” sets enable us to take into account instability of the membership and non-membership degrees with a circular area & its radius. In this study, we first introduce Interval Valued CIF (IVCIF) sets and their arithmetic operations to better incorporate the uncertainty and cover a broader domain. Then, we introduce a novel IVCIF Analytic Hierarchy Process (AHP) method and apply it to evaluate Digital Transformation (DT) projects with complex nature. DT projects requiring fundamental changes in processes, business models and cultures of the companies, contribute a significant value to the companies and increase their market shares; so that they can achieve long term success and competitive advantage. On the other hand, DT problems which are usually ill-defined and include incomplete information based on human judgments, necessitate fuzzy representation. For the success of a digital transformation and to contribute excellence in engineering applications, DT projects should be carefully analyzed. For these reasons, we focus on DT project evaluation problem in application. Also, sensitivity & comparative analyses are performed.

Intuitionistic Fuzzy AHP and WASPAS to Assess Service Quality in Online Transportation

Indonesia is currently entering a new normal era; this requires people to adapt to the clean-living habit in accordance with health standards in order to carry out normal activities. At the same time, online transportation services have reopened for activity. The service quality provided by online ride-hailing companies (i.e., ojek) such as Gojek, Grab, and Maxim must now consider matters relating to user safety. This study proposes Multi Criteria Decision Making (MCDM) as a method for assessing the service quality of online transportation service providers and uses the Pandemic-SERVQUAL 4.0 model. Pandemi-SERVQUAL 4.0 model adds two new criteria, namely "pandemic" and "industry 4.0". The addition of two new criteria that are more relevant to the current circumstances will increase the accuracy of the research. This study aims to propose the integration of Interval Valued Intuitionistic Fuzzy Analytical Hierarchy Process (IVIF-AHP) to determine the criteria weight and Interval Valued Intuitionistic Fuzzy Weighted Aggregated Sum-Product Assessment (IVIF-WASPAS) to assess the service quality of several online transportation service providers based on the obtained criteria weights. From the results of the service quality assessment using the integration of IVIF-AHP and IVIF-WASPAS, the ranking of online transportation service providers during the new normal era were Grab-car, Go-car, and Maxim-car.

Optimisation analysis of distribution network planning based on the IVIF-AHP method

Abstract Distribution network planning is an important task in the process of power grid construction and development. Scientific and rational planning is the key factor for the economic construction and reliable operation of the power grid. Aiming at the difficulty in quantifying the weight of distribution network planning schemes, a comprehensive evaluation method of distribution network planning schemes based on the interval-valued intuitionistic fuzzy analytic hierarchy process method is proposed. First, a comprehensive evaluation index system is established from the four aspects of power supply, namely reliability, economy, power supply quality and safety of the distribution network. Then, a comprehensive evaluation method of electricity reliability optimised by entropy weight method is adopted by analytic hierarchy process, which considers both subjective situation and objective weighting. At the same time, the comprehensive weight of the aggregation of the criterion layer and the scheme layer is calculated. Finally, the link between the aggregation matrix and the index weights of the criterion layer is used to calculate the weights of the scheme layer so that they can be sorted out. The experimental results show that the effectiveness and feasibility of the planning and analysis indicators and evaluation methods of the method proposed in this paper are verified by a numerical example.

Identifying Critical Factors Affecting the Resilience of Additive Manufacturing Architecture Supply Chain

Building a resilient and stable supply chain has become an important strategy for many countries. Studies have shown that the application of additive manufacturing (AM) technology in construction can help offset the negative impact of “black swan events” on supply chains. This study examines the construction industry based on AM technology and analyzes the impact of changes in the industry chain on the supply chains. The specific factors that affect the resilience of AM construction supply chains were identified through literature research and expert interviews, including 7 dimensions and 21 secondary indicators. An intuitionistic fuzzy analytic hierarchy process (IFAHP) evaluation model was established. Finally, an example of an AM construction manufacturer, YC Enterprise, was introduced to quantify the various factors and determine the weights. The results show that the essence of building a supply chain with AM is creating a closed-loop supply chain. The impact of AM construction manufacturers on supply chain resilience (SCR) is the most critical, followed by that of regulatory authorities and general contractors. The AM construction SCR assessment index system and evaluation method constructed in this paper have important significance in filling the gap in the quantitative evaluation of the impact of AM on supply chains.

An intuitionistic dense fuzzy AHP-TOPSIS method for military robot selection

Land, marine and airborne are the three types of military robots used in the war-field. Land robots are the most crucially considered robots. Selecting a military land robot for a specific purpose is one of the challenging problems for a decision-maker to find the most preferred alternative when it involves fuzziness and uncertainty. Intangible factors are used while selecting the appropriate robotic system as it effectively deals with fuzziness. Intuitionistic dense fuzzy set, which is the combination of intuitionistic fuzzy set and dense fuzzy set, is capable of dealing with intangible factors. This study aims to design the integrated model on intuitionistic dense fuzzy AHP-TOPSIS to choose the most preferable military land robots under various circumstances. Robots for different types of situations, namely bomb disposal, search and rescue, surveillance and reconnaissance and war-fighter are considered. Moreover, the intuitionistic dense fuzzy AHP is utilized to calculate the subjective weights of the criteria and intuitionistic dense fuzzy TOPSIS is used to rank the alternatives. Further, a sensitivity analysis is examined to demonstrate the quality of the outcome and the results are compared with the fuzzy set, intuitionistic fuzzy set, and dense fuzzy set to show the efficiency of the proposed methodology.

A visual analytics approach for multi-attribute decision making based on intuitionistic fuzzy AHP and UMAP

Multi-attribute decision making (MADM) has been extensively explored and applied in many real-world problems. However, comprehending the decision-making process and selecting a satisfactory choice from a large set of alternatives characterized by multiple conflicting attributes impose a significant cognitive burden on decision-makers. A visual analytics approach for MADM (MADM-VA) that integrates visual representations of alternatives with the decision-making analysis process is proposed to solve this problem. Firstly, to ensure the final decision meets the actual needs and expectations of decision-makers, an Intuitionistic Fuzzy Analytic Hierarchy Process based on Nonlinear Programming (IFAHP-NLP) is proposed. This approach directly determines the optimal crisp attribute weight vector according to the preferences of decision-makers and avoids information loss and distortion of attribute weights caused by defuzzification. Next, the Uniform Manifold Approximation and Projection (UMAP) is used to map the high-dimensional weighted normalized decision matrix to two-dimensional space, illustrating the distribution of alternatives. The concept of similarity to the ideal solution is introduced to enhance the interpretability of the generated space. Furthermore, the Voronoi diagram is innovatively adopted to assist decision-makers in gaining a better understanding of the decision-making process and help them visually identify the best choice, which is closest to the positive ideal solution and farthest from the negative ideal solution. Finally, experimental results from two case studies verify that MADM-VA is efficient and reliable.

A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak

The use of emergency departments (EDs) has increased during the COVID-19 outbreak, thereby evidencing the key role of these units in the overall response of healthcare systems to the current pandemic scenario. Nevertheless, several disruptions have emerged in the practical scenario including low throughput, overcrowding, and extended waiting times. Therefore, there is a need to develop strategies for upgrading the response of these units against the current pandemic. Given the above, this paper presents a hybrid fuzzy multicriteria decision-making model (MCDM) to evaluate the performance of EDs and create focused improvement interventions. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique is used to estimate the relative priorities of criteria and sub-criteria considering uncertainty. Then, the intuitionistic fuzzy decision making trial and evaluation laboratory (IF-DEMATEL) is employed to calculate the interdependence and feedback between criteria and sub-criteria under uncertainty, Finally, the combined compromise solution (CoCoSo) is implemented to rank the EDs and detect their weaknesses to device suitable improvement plans. The aforementioned methodology was validated in three emergency centers in Turkey. The results revealed that the most important criterion in ED performance was ER facilities (14.4%), while Procedures and protocols evidenced the highest positive D + R value (18.239) among the dispatchers and is therefore deemed as the main generator within the performance network.

A novel fuzzy group decision-making approach based on CCSD method for thermal insulation board selection problem: A case study

Due to buildings’ high energy consumption and environmental impacts, selecting an appropriate thermal insulation board is crucial in reducing energy consumption in an existing building. Therefore, thermal insulation board selection has become an important issue. This study presents a combined fuzzy group decision-making approach that consists of the integrated fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution, the integrated intuitionistic fuzzy analytic hierarchy process and intuitionistic fuzzy technique for order preference by similarity to ideal solution, and intuitionistic fuzzy technique for order preference by similarity to ideal solution for effectively evaluating thermal insulation boards. However, since these three fuzzy decision-making methods can produce different rankings, decision-making is a complex and challenging process for decision-makers. In order to overcome this problem, correlation coefficient and standard deviation method is utilized to construct the final ranking by integrating these approaches using regression statistics, standard deviations, and correlation coefficients between the closeness coefficients of each alternative in the relevant approach. The proposed approach provides an accurate ranking of thermal insulation boards validated through a real-world case study. Furthermore, the sensitivity analysis indicates that the combinations of different levels of criteria and approaches affect the final ranking. According to the study’s findings, the gray expanded polystyrene foam is the most suitable thermal insulation board in the combined fuzzy group decision-making approach.

Selection of ideal supplier in e-procurement for manufacturing industry using intuitionistic fuzzy AHP

Selection of ideal supplier in e-procurement for manufacturing industry using intuitionistic fuzzy AHP

Selection of ideal supplier in E-procurement for manufacturing industry using Intuitionistic Fuzzy AHP (IF-AHP)

Selection of ideal supplier in E-procurement for manufacturing industry using Intuitionistic Fuzzy AHP (IF-AHP)