Fuzzy Multi-criteria Analysis Research Articles

Assessment of Land Suitability in Perennial Crops using FAHP and GIS in Central Vietnam

Background: Perennial crops including rubber and Thanh Tra grapefruit are highly effective land use that has occupied a large area (nearly 11,000 ha) in Thua Thien Hue province, Central Vietnam. Analyzing land suitability in agricultural production is one of the important tools for determining the effective use of land resources and sustainable development. This study aims to evaluate the land suitability of perennial crops in Phong Dien district, Thua Thien Hue province, Central Vietnam. Methods: The study was conducted in different communes in Phong Dien district, Thua Thien Hue province, Central Vietnam from 2022 to 2023 by collecting secondary and primary data together with soil samples from 45 profiles for analysis and finally application of the fuzzy multi-criteria analysis process (FAHP) tool and geographic information system method (GIS) to evaluate the land suitability. Result: The results indicated that economic criteria played the most important role with weights from 0.068 to 0.343, followed by the social criteria (weights from 0.014 to 0.147) and the environmental criteria (weights from 0.011 to 0.051). With land suitability evaluation, the very high suitability area of rubber and Thanh Tra grapefruit (S1) was 3,144.14 ha and 3,742.29 ha respectively. The FAHP and GIS integrated method is a useful method to assess land suitability for land use of perennial crops based on appropriate assessment of FAO land use requirements.

Market segment evaluation based on fuzzy tools

The paper suggests a hybrid model with simplified and extended schemes for evaluating market segments based on strategic diagnostics methods and fuzzy multi-criteria analysis tools. The developed model's novelty and originality consist of forming a system of evaluation criteria based on the GROT criteria of I. Ansoff and the five forces of the M. Porter model (and in the case of an extended calculation scheme – with their decomposition into sets of relevant sub-criteria) and the use of the latest Fuzzy SBWM method (Fuzzy Extension of Simplified Best-Worst Method) to determine their weighting factors. Expert linguistic evaluations on a defined 7-level term set, followed by their transformation into fuzzy numbers with triangular membership functions, are used to evaluate market segments for each identified criteria (sub-criteria). The Fuzzy SAW method determines fuzzy integral estimates of market segments based on these sub-criteria. A practical case of evaluating the confectionery market segments of Ukraine for the simplified calculation scheme is given. The systematic approach makes it possible to determine the attractiveness of market segments for forming strategic recommendations based on the application of portfolio analysis methods, for developing and implementing diversification and logistic strategies.

Multi-criteria constrained interval type-2 fuzzy decision-making: A space analysis perspective

Practical decision-making problems invariably involve inherent uncertainty in information, making it challenging to obtain precise evaluations. In this research, the utilization of constrained interval type-2 fuzzy sets (CIT2 FSs) enables the representation of complex uncertainty in decision information, and a space analysis approach, called CIT2 fuzzy multi-criteria acceptability analysis (CIT2FMAA), is proposed for conducting reliable decision-making. The CIT2FMAA introduces a novel paradigm for type-2 fuzzy decision-making, wherein CIT2 fuzzy evaluations are acknowledged as spaces of type-1 fuzzy evaluations and processed using type-1 fuzzy operations and methodologies. First, from a space analysis perspective, the type-2 fuzzy measures of logical rank expressions are formalized as CIT2 fuzzy rank acceptability indexes, and the CIT2 fuzzy rank acceptability analysis is developed to rank CIT2 fuzzy numbers. Second, the weighted average of the CIT2 fuzzy numbers is defined, and the CIT2FMAA is proposed to support uncertain multi-criteria decision-making. Subsequently, a sampling algorithm is designed for implementing CIT2 fuzzy rank acceptability analysis and CIT2FMAA. Finally, a linguistic disease diagnosis is performed to demonstrate the efficiency of CIT2FMAA. Compared to traditional type-2 fuzzy decision-making methods, CIT2FMAA is more efficient because it not only derives ranks of alternatives but also provides confidence degrees for those ranks.

Location selection for waste disposal boxes: a geographic information systems based Pythagorean fuzzy multi-criteria decision analysis

Location selection for waste disposal boxes: a geographic information systems based Pythagorean fuzzy multi-criteria decision analysis

ДІАГНОСТИКА СТАНУ ПІДПРИЄМСТВА З ВИКОРИСТАННЯМ НЕЧІТКОГО АНАЛІЗУ

The article develops a methodical approach for assessing the overall state of an enterprise, taking into account the conditions of uncertainty in which it operates. It is based on the application of the strategic diagnostics tools, fuzzy set theory and fuzzy multi-criteria analysis. The article identifies the “state of the enterprise” concept. Diagnostics of the state of the enterprise is divided into two stages namely preliminary analysis of the general state of the enterprise and the stage of the direct assessment. We apply classic methods of strategic analysis and competitive analysis at the stage of preliminary analysis of the general state of the enterprise. The stage of the direct assessment is examined in detail. The study introduces a general algorithm for assessing the overall state of the enterprise by means of the fuzzy set theory tools. The algorithm contains seven stages: Stage 1. Establishing an expert group for assessing the state of the enterprise. Stage 2. Decomposition of the state of the enterprise into local components. Stage 3. Applying the Fuzzy AHP method to determine the importance of local components of the state of the enterprise. Stage 4. Decomposition of each local component of the enterprise’s state into assessment indicators. Stage 5. Applying the Fuzzy AHP method to determine the importance of the assessment indicators. Stage 6. Fuzzy assessment of the state of the enterprise by local components using the Fuzzy SAW method. Stage 7. Calculation of the integral assessment of the state of the enterprise applying the Fuzzy SAW method. The article provides a brief description of each of the above mentioned diagnostic stages. It is emphasized that the state of the enterprise is a multi-vector characteristic of the activity of any enterprise. For assessment, the conditional structure of the state of the enterprise is presented in the form of the local components, on the basis of which it is possible to calculate the integral indicator of the state of the enterprise. Considering the fuzziness of the source data, it is advisable to use expert assessments with their translation into triangular fuzzy numbers for assessing the state of the enterprise based on local components. We suggest applying the Fuzzy AHP method to determine the importance of the local components of the state of the enterprise and their assessment indicators and the Fuzzy SAW method to calculate the integral assessment of the state of the enterprise. Special attention is paid to the issues accompanying the process of assessing the state of the enterprise by means of a fuzzy approach. The results of assessing the state of the enterprise (in dynamics) and their interpretation allows the management of the enterprise to develop recommendations and take measures aimed at improving the local components of the state of the enterprise, and as a result, increase the level of the overall condition of the enterprise.

Integrating fuzzy multi-criteria analysis for sustainable configuration of an on-grid hybrid renewable energy system: case study of Tunisia

Integrating fuzzy multi-criteria analysis for sustainable configuration of an on-grid hybrid renewable energy system: case study of Tunisia

Integrating fuzzy multi-criteria analysis for sustainable configuration of an on-grid hybrid renewable energy system: case study of Tunisia

Integrating fuzzy multi-criteria analysis for sustainable configuration of an on-grid hybrid renewable energy system: case study of Tunisia

Методичний інструментарій оцінювання загального стану підприємства

The aim of the article is to generalize the methodical instruments for assessing the general state of enterprise on the basis of taking into account its multi-vector nature. There is a large array of effective methods of comprehensive analysis and diagnostics of the general condition of the enterprise. Their combination will allow you to get an objective assessment and develop recommendations for optimizing the enterprise’s activities. The paper provides a general overview of methods and techniques for assessing the state of enterprise: SWOT analysis, PEST analysis, SPACE analysis, matrix methods, methods of multi-criteria analysis, graphical methods, methods of expert assessment, methods based on the theory of fuzzy sets, etc. A brief description of some of the presented assessment methods (advantages and disadvantages) is provided. It is noted that the efficiency of assessment of the state of enterprise is increased through the use of methods of fuzzy multi-criteria analysis, which allow the analyst to partially reduce the uncertainty of the original data array. Attention is focused on the problems that accompany the process of assessing the state of enterprise. The relevance of systematic diagnostics of the state of enterprise for control and timely productive response to negative dynamics, determination of strategic directions of development of enterprise is substantiated, since the activity of domestic enterprises currently takes place in conditions of a high level of uncertainty. It is noted that taking into account the multi-vector nature of the indicator of «state of enterprise» is the main prerequisite for conducting an effective assessment of the general state of enterprise, therefore, the identification of structural components of the state of enterprise with possible variation depending on a number of factors requires further research. The combination of classical and innovative methods, in particular fuzzy analysis, provides the analyst with instruments for assessing the state of the enterprise, taking into account its multi-vector nature.

Assessment of technical and financial challenges for renewable energy project alternatives

The purpose of this study is to assess technical and financial challenges for renewable energy project alternatives with a novel model. Firstly, a set of technical and financial challenges is created by considering the results of the literature evaluation. After that, the weights of these values are computed by Sine Trigonometric Pythagorean Fuzzy (ST-PFN) DEMATEL. The next step includes the ranking of six renewable energy alternatives with interval valued Spherical fuzzy multicriteria analysis with ratio and categorical data (SF MAIRCA) approach. Entropy and ARAS methodology are also considered to make comparative evaluation. Similarly, sensitivity analysis is also conducted for 10 different cases. It is concluded that the analysis results of all methods are the same. Therefore, it is identified that the findings of the proposed model are reliable and coherent. Identification of the most crucial technical and financial challenges of the renewable energy projects is the most important contribution of this manuscript. Furthermore, preferring the sine trigonometric structure in the proposed model will provide superiority to this model in many respects. It is concluded that difficulty in accessing finance for local projects is the most significant challenge for renewable energy investments. Moreover, competitive pricing of renewable sources is another critical issue in this regard. Additionally, it is identified that solar is the most successful renewable energy alternative to overcome technical and financial challenges.

Understanding the exchange process between ground and surface water using mini drive point piezometer and mathematical models to identify suitable managed aquifer recharge sites.

In the current study, subsurface characteristics within the complex formation of the Shilabati basin system of West Bengal, India, extending over an area of 3888 km2, have been estimated using a cost-effective piezometer and MIKE FEFLOW package based on a steady-state numerical model. Pore size and fine particle content of streambeds are affected by two opposing flow contraptions. Such opposite flow conditions are likely to affect the hydraulic conductivity of the streambed. However, analogies of the hydraulic conductivity (Kh) of streambeds for losing and gaining streams have not been well documented in the recent past. The Kh value from the piezometer has been highest at the Dakshin Pairachali site (6.765 m/day), with the stream gaining water from the discharge of the local aquifer. Analysis of the stream-aquifer interaction using the FEFLOW model has allowed us to understand the groundwater water head of the basin ranging from 160.33 to 0.32 m.a.s.l (meters above sea level). The present study also constitutes the first attempt for the identification of suitable sites for the implementation of managed aquifer recharge (MAR) technology in West Bengal, India, to manage extreme drought events. The suitable sites have been identified by means of three fuzzy multi-criteria decision analysis based on nine criteria: river discharge, moisture content, porosity, drainage type, rainfall, land use type, geology, aquifer material, and hydraulic conductivity. To design a radial collector well and infiltration gallery for the selected site in an anisotropic, homogeneous, unconfined, and semi-infinite aquifer near a fully penetrating stream, a pumping test has been conducted to optimize a safe yield of 12.096 MLD (megaliters per day).

Identifying Optimal Locations for Hardwood CLT Plants in Tennessee: Application of a Spatially Explicit Framework

Abstract The prospect of using mass timber products, such as cross-laminated timber (CLT), for building material has increased in recent years because of the advantage of these products over their substitutes in terms of structural rigidity, cost efficiency, and climate benefits. However, the American National Standard developed for CLT currently applies to softwood only. With the expected increase in the market for CLT, the supply chain needs to address the projected rise in demand for hardwood as well. Promoting the production of hardwood mass timber like CLT requires studying the feasibility of quality hardwood lumber supply and identifying the optimal locations for investing capital in CLT manufacturing plants. By presenting a case from Tennessee, this study provides a spatially explicit framework to use a variety of factors such as transportation networks, proximity to sawmills, sawmill capacity, and roundwood supply to identify optimal CLT plant locations. Specifically, fuzzy multicriteria analysis was used to identify potential locations, which provided inputs for a location-allocation model to identify optimal locations for CLT plants. Among the several potential locations, three optimal locations suitable for CLT plants were identified with 12,504 thousand cubic feet (MCF) annual production potential of CLT panels in Tennessee. Although increasing transportation distance for lumber procurement would increase CLT production capacity, it would also result in increased lumber supply costs. Potential investors and regional planners interested in using hardwood forest products can benefit from these findings to locate suitable sites for new investment.

Flat Roofs Renovation Planning on Public Buildings Using Fuzzy Multi-Criteria Analysis

Renovation of flat roofs typically involves repairing or replacing the existing roof to improve its performance and extend its lifespan. The renovation process may include a range of tasks depending on the condition of the roof, such as repairing leaks, replacing damaged or deteriorated materials, adding insulation, or upgrading drainage systems. This research aim was to establish the priority of renovation of flat roofs of the public building based on the principles of multi-criteria analysis and fuzzy set theory, using the multi-criteria method PROMETHEE II in fuzzy logic form (F-PROMETHEE II). The proposed approach is adequate due to its ability to transform the uncertain and vague information received from an expert into a fuzzy number. This way, the objective outcome can be obtained, the criteria conflict removed and the alternatives ranking and mutual comparison enabled. It was necessary to analyze the existing literature, the flat roofs of a public building in terms of their current condition, and define the main goals and criteria for the roof renovation project. Based on the defined goals and criteria, the roofs are evaluated and ranked according to the priority for renovation. The planning process of renovation of flat roofs was carried out specifically on the building of the Faculty of Civil Engineering, Architecture and Geodesy in Split.

RETRACTED ARTICLE Fuzzy multicriteria analysis of “Better Cotton” farmers’ adoption and experts’ recommendation on cotton pest and disease management practices

RETRACTATION The SJAR Editorial Board, following the Guide to Good Practices of Editorial CSIC and the international recommendations of editorial ethics, due to a conflict of duplicity, has agreed to formally retract the following article: Fuzzy multicriteria analysis of “Better Cotton” farmers’ adoption and experts’ recommendation on cotton pest and disease management practices (2022), by Absar M. Jiskani, Manzoor A. Abro, M. Ibrahim Khaskheli and Khadim H. Wagan. Spanish Journal of Agricultural Research, Volume 20, Issue 4, e1006. https://doi.org/10.5424/sjar/2022204-18953. The retractation is based on the following: in addition to authorship and funding disputes that we cannot arbitrate, the article was submitted to two journals at the same time: Spanish Journal of Agricultural Research (SJAR) and Academia Journal of Agricultural Research (AJAR). This evidence came to light once the article was published in SJAR. The article was also published in AJAR 10(3), 042-053, March 2022: Fuzzy multi-critaria analysis of better Cotton farmers' adoption and experts' recommendation on Cotton pest and disease management practices, by Absar Mithal Jiskani, Noor Nabi Bhutto and Abdul Rehman, https://www.academiapublishing.org/journals/ajar/content/2022/Mar.htm, DOI: 10.15413/ajar.2021.0128. Currently there is neither access to the pdf nor there is any information. Only the author Absar M. Jiskani is common to both articles. Both journals indicate in their instructions the same. In the case of AJAR (https://www.academiapublishing.org/journals/ajar/policy.htm), “Authors must not submit the same work, in whole or in part, to two places of publication at the same time, or at any time while the manuscript is under review at ACADEMIA PUBLISHING”. In the case of SJAR (https://revistas.inia.es/index.php/sjar/about/submissions): “Submission of a manuscript implies the work described has not been published previously in any language (except in a book of abstracts, in the proceedings of a scientific meeting or as part of a thesis); the work is not under consideration for publication elsewhere, etc. “. When comparing the submitted version to SJAR to the article published in AJAR (pdf file supplied by the claimant), both articles present more than 80% similarity, with the abstract, tables and figures being identical. This similarity is unacceptable.

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

The high contagion rates of COVID-19 and the limited amounts of vaccines forced public health authorities to develop vaccinations strategies for minimizing mortality, avoiding the collapse of health care infrastructure, and reducing their negative impacts to societies and economies. We propose a Multi Criteria Group Decision Making for prioritizing a set of COVID-19 vaccination alternatives, under a picture fuzzy environment, where the weights for Decisions Experts (DE) and criteria are unknown. A panel of six DEs assess six criteria for prioritizing four groups for vaccination. The weights for DE and criteria are handled in the form of fuzzy sets. Three types of weights are calculated: subjective, objective, and mixture weights.According to our results, three out of the six criteria hold 60% of the strategic importance: 1) allocation and distribution, 2) COVID-19 strains and 3) capabilities and infrastructures. However, persons with comorbidities became the group with the highest priority, followed by essential workers, women, and adults older than 40 years. Governments, decision makers, and policy makers can find rigorous scientific evidence for articulating effective vaccinations campaigns from this work, and contribute to minimize undesired outputs, such as high mortality rates or collapse of hospitals.

A double fuzzy multi-criteria analysis to evaluate international high-performance aircrafts for defense purposes

This paper contributes the first-known study involving international military high-performance aircrafts together with their weaponry systems for defense purposes.This technical study had the invaluable help from an advisory group of instructor pilots whose expertise in combat aircrafts allowed the calculation of the relative importance of qualitative criteria playing a key role in each analysis. The combination of a modified version of Analytic Hierarchy Process (AHP; to determine the weights of the criteria) and Technique for Order of Preference by Similarity to ideal Solution (TOPSIS; to assess each set of alternatives) approaches with fuzzy logic becomes especially appealing for this case of study.The best scores were obtained by the F-16 jet and the SCALP EG missile. First, the F-16 (with a defuzzified TOPSIS coefficient of 0.95) was closely followed by both jets Su-35 (2nd position, with a coefficient equal to 0.93) and Su-30 (third position, 0.89). However, the difference between the SCALP EG (1.02) and its chasing alternative, the Kh-59M (0.65), was significantly greater. Such results were reinforced by sensitivity analyses through a combination of fuzzy AHP-VIKOR.

Comparison of hospital service performances under COVID-19 pandemics for pilot regions with low vaccination rates

It is essential to measure the quality and performance of health centers and propose policies in order for health services to continue without interruption during the pandemic period and for the continuous and proper implementation of new procedures in hospitals with COVID-19.The measurement of service quality and performance in hospitals should be provided not only for the smooth flow of health services that are vital for individuals but also for the elimination of hesitations in the treatment and vaccination processes related to COVID-19. Previously, models have been proposed by introducing some criteria to measure and evaluate hospital service performance in some extraordinary conditions, but such a study has not yet been put forward under pandemic conditions. Starting from this point, we aim to fill the gap in the literature by conducting a measurement study for hospitals in the pilot region, where COVID-19 cases are common but vaccination is observed at low rates. For this aim, the evaluation criteria are gathered under basic dimensions as in SERVPERF (Service Performance), which is a widely used tool for measuring service quality and a fuzzy multi-criteria decision analysis is proposed to measure the service performance of state hospitals for a pilot region. In the proposed methodology, the integrated methods consisting of CRITIC-TOPSIS have been extended with fermatean fuzzy sets. Expert opinions are taken via questionaries to determine hospital service performances. Based on the results obtained from the hospitals in the pilot region, the policies and strategies to be adopted by the hospitals serving under pandemic conditions worldwide to increase the service quality have been put forward. Additionally, the sensitivity of the parameters in the problem is measured, and then the validity of the obtained results is also validated. According to the results, assurance is determined as the most important main service performance factor during the pandemic period. So, the managers should develop strategies to address people's concerns about vaccines and increase people's trust in hospitals.

A novel MCDM model for warehouse location selection in supply chain management

The present investigation reveals a novel method for the evaluation of warehouse location for leagile supply chain entailing Fuzzy Multi Criteria Analysis (FMCA). An attempt has been made to apply the concept of decision theory for selecting the warehouse under contradictory criteria. Aggregate Modified Weighted Value (MWV) of normalized score of alternative is determined to evaluate Benefit Cost Ratio (BCR) which is considered as the warehouse selection index. The proposed algorithm is illustrated with a suitable numerical example to adjudge its desirable importance in capability and practicability. It also ensured that the achieved result clearly matches with those of previous research works. Finally, sensitivity analysis has been carried out that justify and supports the application of proposed algorithm in finding the most favorable outcome to the selection problem of warehouse location.

Analysis and evaluation of Indian industrial system requirements and barriers affect during implementation of Industry 4.0 technologies

In recent years, competition among the Indian manufacturing industries (IMI) has increased enormously in the global market. The current uncertainty in the market context is characterised and governed by the customised requirements of the customers. Thus, the manufacturing system in the industries should be capable of adapting the parameters like flexibility in scalability, variety, agility, system responsiveness, inter-connectivity, automatic data exchange with communication among the manufacturing systems, transparency and human–machine interaction, which are the main components and principles of Industry 4.0 (I4.0). Thus, adopting I4.0 plays a vital role to corroborate its long-term survival in the global marketplace. However, very few research work considerations contribute towards the issues induced during the adoption of I4.0 in manufacturing industries. This paper aims to minimise the gap between the existing Industrial System Requirements (ISRs) and the challenges faced during implementing I4.0 technologies in existing Industries. The identified ISRs and barriers were evaluated and analysed based on the data set collected from a questionnaire-based survey. Fuzzy multi-criteria analysis is conducted to identify the most weighted ISRs and barriers and ranked them concerning their importance. Furthermore, the inter-item correlation between both of them is analysed. This research work offers the researchers, practitioners, and industrialists an opportunity to formulate multi-criteria decision making (MCDM) problems through numerous case studies and prioritise the top barriers, system requirements and the inter-relationship shared between them.

Customer-oriented product design using an integrated neutrosophic AHP & DEMATEL & QFD methodology

With the increasing product variety, companies aim to become better than their competitors by providing a superior product developed with a customer-oriented product design approach and a quality strategy. In order to achieve this, companies should well understand customer expectations and quickly be able to convert these expectations to technical characteristics. Since the expectations consist of mostly subjective judgments, this evaluation process contains vagueness and impreciseness. A triplet represents the uncertainty in subjective judgments: the degrees of belongingness or Truthiness (T), non-belongingness or Falsity (F), and indeterminacy (I). For this reason, in this paper, a neutrosophic Quality Function Deployment (QFD) methodology based on neutrosophic AHP and neutrosophic DEMATEL is developed and applied to the design of a car seat. In this methodology, the weighting of customer requirements is performed by neutrosophic AHP. The relationships among the technical characteristics are determined by neutrosophic DEMATEL for the customer-oriented product design, considering both impreciseness in the data and indeterminacy of the decision-makers. In other words, the contribution of this paper is that the proposed methodology provides better integration of the voice of customers into technical characteristics through a practical fuzzy multi-criteria decision analysis. Based on the results, it is revealed that seat height is the most important technical characteristic, followed by vertical travel range and horizontal travel range. Moreover, validity and verification of the proposed methodology have been tested with other methods presented in the literature. Sensitivity analyses have been carried out to show the flexibility of the given decisions under different cases. Lastly, possible implications on theoretical and managerial aspects have been discussed.

Hybrid Fuzzy Multi-Criteria Analysis for Selecting Discrete Preferable Groundwater Recharge Sites

This study proposes a hybrid fuzzy multi-criteria methodology for the selection of the most preferable site for applying managed aquifer recharge (MAR) systems by utilizing floodwaters. The use of MAR can increase water resources for later water utilization in case of drought. In this multi-criteria problem, seven recharge sites are under consideration, based on nine criteria, aiming to make a final list of their relative ranking. A fuzzy analytic hierarchy process (FAHP) based on the logarithmic fuzzy preference programming (LFFP) method is used to determine the weights of criteria. LFFP is an optimization-based method that produces a priority vector from a fuzzy pairwise comparison matrix. Furthermore, fuzzy inference systems (FIS) based on the Mamdani approach are used to estimate the rating of each alternative with respect to the criterion examined, and then the final evaluation of the alternatives is obtained. A FIS is a fuzzy if–then rule-based system where the experts’ qualitative knowledge is translated into numerical reasoning for each individual criterion. The proposed methodology is applied in the aquifer system of the agricultural plain located to the southeast of the city of Xanthi in the Prefecture of Xanthi, NE Greece.