Journal of Intelligent & Fuzzy Systems - Volume 42, issue 1

Authors: Şahin, Bünyamin | Şahin, Abdulgani

Article Type: Research Article

Abstract: In a graph G , a vertex v is dominated by an edge e , if e is incident with v or e is incident with a vertex which is a neighbor of v . An edge-vertex dominating set D is a subset of the edge set of G such that every vertex of G is edge-vertex dominated by an edge of D . The ev -domination number equals to the number of an edge-vertex dominating set of G which has minimum cardinality and it is denoted by γ ev  (G …). We here analyze double edge-vertex domination such that a double edge-vertex dominating set D is a subset of the edge set of G , provided that all vertices in G are ev -dominated by at least two edges of D . The double ev -domination number equals to the number of an double edge-vertex dominating set of G which has minimum cardinality and it is denoted by γ dev  (G ). We demonstrate that the enumeration of the double ev -domination number of chordal graphs is NP-complete. Moreover several results about total domination number and double ev -domination number are obtained for trees. Show more

Keywords: Trees, edge-vertex domination, double edge-vertex domination, total domination, domination

DOI: 10.3233/JIFS-219180

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 121-128, 2022

Authors: Bilgiç, Ceyda Tanyolaç | Bilgiç, Boğaç | Çebi, Ferhan

Article Type: Research Article

Abstract: It is significant that the forecasting models give the closest result to the true value. Forecasting models are widespread in the literature. The grey model gives successful results with limited data. The existing Triangular Fuzzy Grey Model (TFGM (1,1)) in the literature is very useful in that it gives the maximum, minimum and average value directly in the data. A novel combined forecasting model named, Moth Flame Optimization Algorithm optimization of Triangular Fuzzy Grey Model, MFO-TFGM (1,1), is presented in this study. The existing TFGM (1,1) model parameters are optimized by a new nature- inspired heuristic algorithm named Moth-Flame Optimization …algorithm which is inspired by the moths flying path. Unlike the studies in the literature, in order to improve the forecasting accuracy, six parameters (λ L , λ M , λ R , α , β and γ ) were optimized. After the steps of the model is presented, a forecasting implementation has been made with the proposed model. Turkey’s hourly electricity consumption data is utilized to show the success of the prediction model. Prediction results of proposed model is compared with TFGM (1,1). MFO-TFGM (1,1) performs higher forecasting accuracy. Show more

Keywords: Grey forecasting, MFO-TFGM(1, 1), parameter optimization, moth-flame optimization, TFGM (1, 1)

DOI: 10.3233/JIFS-219181

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 129-138, 2022

Authors: Fan, Ching-Lung

Article Type: Research Article

Abstract: Project managers supervise projects to ensure their smooth completion within a stipulated time frame and budget while guaranteeing construction quality. The relationships of various attributes with quality can be quantified and classified to facilitate such supervision. Therefore, this study used a data mining algorithm to analyze the relationships between defects, quality levels, contract sums, project categories, and progress in 1,015 inspection projects. In the first part, association rule mining (ARM), an unsupervised data mining approach, was used to obtain 11 rules relating two defect types (i.e., quality management system and construction quality) and determine the relationships between the four attributes …(i.e., quality level, contract sum, project category, and progress). The resulting association rule may be beneficial for construction management because project managers can use it to determine the correlations between defects and attributes. In the second part, supervised data mining techniques, namely neural network (NN), support vector machine (SVM), and decision tree (C5.0 and QUEST) algorithms, were applied to develop a classification model for quality prediction. The target variable was quality, which was divided into four levels, and the decision variables comprised 499 defects, 3 contract sums, 7 project categories, and 2 progress variables. The results indicated that five defects were important. Finally, the four indicators of gain chart, break-even point (BEP), accuracy, and area under the curve (AUC) were calculated to evaluate the model. For the SVM model, the actual value predicted by the gain chart was 96.04%, the BEP was 0.95, and the AUC was 0.935. The SVM yielded optimal classification efficiency and effectively predicted the quality level. The data mining model developed in this study can serve as a reference for effective construction management. Show more

Keywords: Data mining, association rule, classification, quality level, defect

DOI: 10.3233/JIFS-219182

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 139-153, 2022

Authors: Kuchta, Dorota | Zabor, Adam

Article Type: Research Article

Abstract: An analysis of the scientific literature on project cash flow control and fuzzy modelling shows that project cash flows are modelled using only basic approaches drawn from fuzzy theory, which may distort the credibility of the model. In this paper, we therefore propose to use the whole spectrum of fuzzy arithmetic, and to select operations that suit the nature of the cash flows in question, their dependencies and the preferences of the project manager. An analysis of the literature also shows that in practically all existing models of project costs and cash flow management, project costs and cash flows are …treated at a very high level of generality (without considering the various types of project, factors influencing their variability and signals warning of imminent cash-related problems), and estimations are not updated on an ongoing basis throughout the duration of the project. The results of a survey performed with the participation of 100 project managers show that this simplistic view of project cash flows may be distorting, and cannot guarantee the development of an efficient project cost and cash flow control system. We propose an approach that at least partially compensates for these drawbacks: it differentiates between types of project cash flows and the factors and triggers affecting changes in cash flows. Two case studies are used for a an initial verification of the approach. The paper concludes with suggestions for further research perspectives. Show more

Keywords: Fuzzy cash flow, project cash flow control, project cash flow types

DOI: 10.3233/JIFS-219183

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 155-168, 2022

Authors: Dizbay, İkbal Ece | Öztürkoğlu, Ömer

Article Type: Research Article

Abstract: Reaching a high vaccination coverage level is of vital essence when preventing epidemic diseases. For mandatory vaccines, the demand can be forecasted using some demographics such as birth rates or populations between certain ages. However, it has been difficult to forecast non-mandatory vaccine demands because of vaccine hesitation, alongside other factors such as social norms, literacy rate, or healthcare infrastructure. Consequently, the purpose of this study is to explore the predominant factors that affect the non-mandatory vaccine demand, focusing on the recommended childhood vaccines, which are usually excluded from national immunization programs. For this study, fifty-nine factors were determined and …categorized as system-oriented and human-oriented factors. After a focus group study conducted with ten experts, seven system-oriented and eight human-oriented factors were determined. To reveal the cause and effect relationship between factors, one of the multi-criteria decision-making methods called Fuzzy-DEMATEL was implemented. The results of the analysis showed that “Immunization-related beliefs”, “Media/social media contents/messaging”, and “Social, cultural, religious norms” have a strong influence on non-mandatory childhood vaccine demand. Furthermore, whereas “Availability and access to health care facilities” and “Political/ financial support to health systems” are identified as cause group factors, “Quality of vaccine and service delivery management” is considered an effect group factor. Lastly, a guide was generated for decision-makers to help their forecasting process of non-mandatory vaccine demands to avoid vaccine waste or shortage. Show more

Keywords: Vaccination demand, factor relationship, fuzzy DEMATEL

DOI: 10.3233/JIFS-219184

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 169-180, 2022

Authors: Sarucan, Ahmet | Baysal, Mehmet Emin | Engin, Orhan

Article Type: Research Article

Abstract: The membership functions of the intuitionistic fuzzy sets, Pythagorean fuzzy sets, neutrosophic sets and spherical fuzzy sets are based on three dimensions. The aim is to collect the expert’s judgments. Physicians serve patients in the physician selection problem. It is difficult to measure the service’s quality due to the variability in patients’ preferences. The patients physician preference criteria is differing and uncertainties. Thus, solving this problem with fuzzy method is more appropriate. In this study, we considered the physician selection as a multi-criteria decision-making problem. Solving this problem, we proposed a spherical fuzzy TOPSIS method. We used the five alternatives …and eight criteria. The application was performed in the neurology clinics of Konya city state hospitals. In addition, we solved the same problem by the intuitionistic fuzzy TOPSIS method. We compared the solutions of two methods with each other. We found that the spherical fuzzy TOPSIS method is effective for solving the physician selection problem. Show more

Keywords: Multi-criteria decision-making, spherical fuzzy, intuitionistic fuzzy, TOPSIS, physician selection

DOI: 10.3233/JIFS-219185

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 181-194, 2022

Authors: Ozceylan, Eren | Ozkan, Baris | Kabak, Mehmet | Dagdeviren, Metin

Article Type: Research Article

Abstract: In addition to the well-known fuzzy sets, a novel type of fuzzy set called spherical fuzzy set (SFS) is recently introduced in the literature. SFS is the generalized structure over existing structures of fuzzy sets (intuitionistic fuzzy sets-IFS, Pythagorean fuzzy sets-PFS, and neutrosophic fuzzy sets-NFS) based on three dimensions (truth, falsehood, and indeterminacy) to provide a wider choice for decision-makers (DMs). Although the SFS has been introduced recently, the topic attracts the attention of academicians at a remarkable rate. This study is the expanded version of the authors’ earlier study by Ozceylan et al. [1 ]. A comprehensive literature review …of recent and state-of-the-art papers is studied to draw a framework of the past and to shed light on future directions. Therefore, a systematic review methodology that contains bibliometric and descriptive analysis is followed in this study. 104 scientific papers including SFS in their titles, abstracts and keywords are reviewed. The papers are then analyzed and categorized based on titles, abstracts, and keywords to construct a useful foundation of past research. Finally, trends and gaps in the literature are identified to clarify and to suggest future research opportunities in the fuzzy logic area. Show more

Keywords: Spherical fuzzy sets, fuzzy logic, literature review

DOI: 10.3233/JIFS-219186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 195-212, 2022

Authors: Türkbayrağí, Mert Girayhan | Dogu, Elif | Esra Albayrak, Y.

Article Type: Research Article

Abstract: Automotive aftermarket industry is possessed of a wide product portfolio range which is in the 4th rank by its worldwide trade volume. The demand characteristic of automotive aftermarket parts is volatile and uncertain. Nevertheless, the cause-and-effect relationship of automotive aftermarket industry has not been defined obviously heretofore. These conditions bring automotive aftermarket sales forecasting into a challenging process. This paper is composed to determine the relevant external factors for automotive aftermarket sales based on expert reviews and to propose a sales forecasting model for automotive aftermarket industry. Since computational intelligence techniques yield a framework to focus on predictive analytics …and prescriptive analytics, an artificial neural network model constructed for Turkey automotive aftermarket industry. Artificial intelligence is a subset of computational intelligence that focused on problems which have complex and nonlinear relationships. The data which have complex and nonlinear relationships could be modelled successfully even though incomplete data in case of implementation of appropriate model. The proposed ANN model for sales forecast is compared with multiple linear regression and revealed a higher prediction performance. Show more

Keywords: Sales forecasting, automotive aftermarket, artificial neural network, ANN, predictive analytics

DOI: 10.3233/JIFS-219187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 213-225, 2022

Authors: Çakır, Esra | Ulukan, Ziya | Acarman, Tankut

Article Type: Research Article

Abstract: Determining the shortest path and calculating the shortest travel time of complex networks are important for transportation problems. Numerous approaches have been developed to search shortest path on graphs, and one of the well-known is the Dijkstra’s label correcting algorithm. Dijkstra’s approach is capable of determining shortest path of directed or undirected graph with non-negative weighted arcs. To handle with uncertainty in real-life, the Dijkstra’s algorithm should be adapted to fuzzy environment. The weight of arc -which is the vague travel time between two nodes- can be expressed in bipolar neutrosophic fuzzy sets containing positive and negative statements. In addition, …the weights of arcs in bipolar neutrosophic fuzzy graphs can be affected by time. This study proposes the extended Dijkstra’s algorithm to search the shortest path and calculate the shortest travel time on a single source time-dependent network of bipolar neutrosophic fuzzy weighted arcs. The proposed approach is illustrated, and the results demonstrate the validity of the extended algorithm. This article is intended to guide future shortest path algorithms on time-dependent fuzzy graphs. Show more

Keywords: Graph theory, Dijkstra’s algorithm, time-dependent shortest path problem, shortest travel time, fuzzy set theory, bipolar neutrosophic fuzzy number

DOI: 10.3233/JIFS-219188

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 227-236, 2022

Authors: Çakır, Esra | Taş, Mehmet Ali | Ulukan, Ziya

Article Type: Research Article

Abstract: A pandemic was declared in 2020 due to COVID-19. The most important way to deal with the virus is mass vaccination which is a complex task in terms of fast transportation and process management. Hospitals and other health centers are appropriate for vaccination process. In addition, in order to protect other patients from COVID-19 and provide rapid access to vaccines, mobile vaccination clinics can also be considered. In this study, the location assignments of mobile vaccination clinics that can serve some regions of three cities in Turkey are examined. The linear formulation of the problem is given, and the multi-facility …location problem for COVID-19 vaccination is investigated with Lagrange relaxation and modified saving heuristic algorithm. For the proposed fuzzy MCDM integrated saving heuristic, the importance of candidate locations is calculated with the aid of decision makers who give their views in spherical bipolar fuzzy information. The results of different approaches are compared, and it is intended to guide future studies. Show more

Keywords: Spherical bipolar fuzzy set, COVID-19, lagrange relaxation, modified saving heuristic algorithm, multi-facility location problem, mobile vaccination clinics

DOI: 10.3233/JIFS-219189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 237-250, 2022

Authors: Gerasimenko, Evgeniya | Kureichik, Vladimir V.

Article Type: Research Article

Abstract: Nowadays, various emergencies that are human-made or natural occur widely and threaten people’ lives and health. One of the most important evacuation tasks is the minimum cost lexicographic flow modelling task, which allows aggrieved to be transported to safe areas along the optimal transportation routes, taking into account the priority of shelters. It is inevitable that when modelling an evacuation scenario, an expert will encounter difficulties in setting network parameters due to the inherent uncertainty of a network, the rapid change in the nature of the movement, etc. Intuitionistic fuzzy sets allow simulating doubts and uncertainty of a decision-maker when …choosing a membership function. Due to the increasing complexity of the decision-making problems, experts cannot assess all the network parameters correctly because much specific knowledge is required, and each expert cannot be familiar with all attributes equally. Therefore, different decision-makers should have different values for various attributes. The algorithm proposed incorporates the search for the order of reliable shelters according to the modified TOPSIS method and the minimum cost paths in intuitionistic fuzzy conditions based on the non-standard subtraction operation. A case study is conducted to verify the proposed algorithm. Show more

Keywords: Lexicographic evacuation flow, intuitionistic network, fuzzy evacuation modeling

DOI: 10.3233/JIFS-219190

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 251-263, 2022

Authors: Yaşlı, Fatma | Bolat, Bersam

Article Type: Research Article

Abstract: Occupational safety problems are no longer acceptable for any industrial environment. Lack of comprehensive and reliable evaluations for occupational safety causes many undesired events and harm to employees during the industrial process. In this study, it is aimed to develop an applicable risk analysis methodology for evaluating the undesired occupational events that occurred in the multi-process system where no historical accident records. The difficulty in obtaining and analyzing the data required for the determination of the occupational safety risks especially in the manually executed processes has been overcome with the Bayesian Network and interval type-2 fuzzy sets by using the …expert judgments. While BN enables to development of a comprehensive reasoning approach about the occurrence of the events, interval type-2 fuzzy sets better represent the ambiguity in the judgments by covering the uncertainty in a wider mathematical range with less computational effort according to other fuzzy sets. During multi-processes in industrial activity, various occupational undesired events may occur, including rare events with very serious consequences or frequent events with very low severity consequences. To able to consider all kinds of events occurring in an industrial environment from a holistic risk perspective, a novel fuzzy scale for specifying the probability and consequence of the events are proposed by the interval type-2 fuzzy numbers. Therefore, all undesired events regardless the probability and consequence which may occur during the multi-processes in a system and the main root causes of these events can be observed within the proposed methodology. A case study is used to emphasize the effect of the proposed methodology for risk analysis of occupational safety in underground mining. The results have indicated that occupational safety education is the most contributing factor to occurring the undesired occupational events in underground mining. We believe that this study could help evaluate the safety risk of the multi-process systems comprehensively and holistically and proposing strategic planning for mitigating the occupational safety risks. Show more

Keywords: Bayesian Network, interval type-2 fuzzy sets, occupational safety, risk analysis, underground mining

DOI: 10.3233/JIFS-219191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 265-282, 2022

Authors: Temelcan, Gizem | Gonce Kocken, Hale | Albayrak, Inci

Article Type: Research Article

Abstract: Solving multi-objective linear programming (MOLP) problems and fully fuzzy multi-objective linear programming (FFMOLP) problems involves the trade-off process among several objectives. A new algorithm extended where FFMOLP problems are solved using a 2-player zero-sum game approach to deal with this case. Firstly, The FFMOLP problem is separated into a certain number of fully fuzzy linear programming (FFLP) problems and each is solved by applying any method. After forming a ratio matrix, a game theory approach is applied for finding the weights of objective functions and a weighted LP problem is constructed by these weights. Solving the weighted LP problem, a …fuzzy compromise solution of the FFMOLP problem is found. Constructing different ratio matrices, it is also possible to obtain more than one compromise solution to be offered to the decision-maker(s). Some examples are given to show the applicability of the algorithm. Show more

Keywords: Fully fuzzy multi-objective linear programming problem, compromise solution, ranking method, distance method and zero-sum game

DOI: 10.3233/JIFS-219192

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 283-293, 2022

Authors: Alkan, Nurşah | Kahraman, Cengiz

Article Type: Research Article

Abstract: A circular intuitionistic fuzzy set (CIFS) recently introduced by Atanassov as a new extension of intuitionistic fuzzy sets is represented by a circle whose radius is r and whose center is composed of membership and non-membership degrees. The idea is similar to type-2 fuzzy sets, which are based on the fuzziness of membership functions with a third dimension. CIFSs help us define membership functions more flexibly, taking into account the vagueness in membership and non-membership degrees. In this study, TOPSIS, which is a multi-criteria decision-making (MCDM) method, is developed under circular intuitionistic fuzzy environment. The proposed CIF-TOPSIS method is …applied to determine the most appropriate pandemic hospital location selection problem. Then, a sensitivity analysis based on criteria weights and the weight of the decision maker’s optimistic and pessimistic attitudes are conducted to check the robustness of the decisions given by the proposed approach. A comparative analysis with the single-valued intuitionistic fuzzy TOPSIS, Pythagorean fuzzy TOPSIS, picture fuzzy TOPSIS methods is also performed to verify the developed approach and to demonstrate its effectiveness. Show more

Keywords: Circular intuitionistic fuzzy sets, intuitionistic fuzzy sets, MCDM, TOPSIS, pandemic, hospital location selection

DOI: 10.3233/JIFS-219193

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 295-316, 2022

Authors: Kilic, Huseyin Selcuk | Kalender, Zeynep Tugce | Yalcin, Ahmet Selcuk | Erkal, Gizem | Tuzkaya, Gulfem

Article Type: Research Article

Abstract: Like the other industries, information technologies are very important tools for the hotels’ success in the tourism industry. Various processes required for the hotel business can be integrated by using a proper system, and simultaneous data transfer among different channels can be facilitated. Due to its contribution in creating value for the customers and the increasing efficiency of the processes, substantial investments in information technologies are planned by the hotel management. Like most operation management problems, evaluation and selection of proper hotel information systems require considering multiple criteria. Also, considering the uncertainty inherent to the problem and difficulties during the …evaluation process, an integrated IVIF-DEMATEL and IVIF-TOPSIS approach is utilized in this paper. The IVIF-DEMATEL is used for the criteria evaluation, and the weight determination phase and IVIF-TOPSIS is used to evaluate hotel information systems alternatives. An application for the Turkish tourism sector’s case is realized, and the results of the methodology are compared with the IVIF-VIKOR approach. Show more

Keywords: Channel manager, hotel information system, IVIF-DEMATEL, IVIF-TOPSIS

DOI: 10.3233/JIFS-219194

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 317-335, 2022

Authors: Hamal, Serhan | Senvar, Ozlem

Article Type: Research Article

Abstract: Many studies have used different financial ratios for financial accounting fraud detection. This study focuses on multicriteria decision-making (MCDM) for ranking 25 financial ratios with respect to six criteria in detecting financial accounting fraud using interval-valued spherical fuzzy sets (IVSFS) and single-valued spherical fuzzy sets (SVSFS) to overcome uncertainties in decision-making process of financial analysts. This study proposes an integrated Analytic Hierarchy Process (AHP) and Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form (MULTIMOORA) approach using IVSFS and SVSFS. Comparative results are obtained and discussed in prioritization of financial ratios for both IVSFS and SVSFS.

Keywords: Financial ratios, financial accounting fraud detection, single-valued spherical fuzzy sets (SVSFS), interval-valued spherical fuzzy sets (IVSFS), analytic hierarchy process (AHP), multi-objective optimization by a ratio analysis plus the full multiplicative form (MULTIMOORA)

DOI: 10.3233/JIFS-219195

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 337-364, 2022

Authors: Sergi, Duygu | Sari, Irem Ucal | Senapati, Tapan

Article Type: Research Article

Abstract: Capital budgeting requires dealing with high uncertainty from the unknown characteristics of cash flow, interest rate, and study period forecasts for future periods. Many fuzzy extensions of capital budgeting techniques have been proposed and used in a wide range of applications to deal with uncertainty. In this paper, a new fuzzy extension of the most used capital budgeting techniques is proposed. In this content, first interval-valued Fermatean fuzzy sets (IVFFSs) are defined, and the algebraic and aggregation operations are determined for interval-valued Fermatean fuzzy (IVFF) numbers. The formulations of IVFF net present value, IVFF equivalent uniform annual value, and IVFF …benefit-cost ratio (B/C) methods are generated. To validate the proposed methods, proposed formulations are illustrated with a hypothetical example, and the results are compared with classical fuzzy capital budgeting techniques. Show more

Keywords: Interval-valued Fermatean fuzzy sets, fuzzy engineering economics, fuzzy net present value, fuzzy equivalent uniform annual value, fuzzy benefit cost ratio

DOI: 10.3233/JIFS-219196

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 365-376, 2022

Authors: Piltan, Farzin | Kim, Jong-Myon

Article Type: Research Article

Abstract: Pipelines are a nonlinear and complex component to transfer fluid or gas from one place to another. From economic and environmental points of view, the safety of transmission lines is incredibly important. Furthermore, condition monitoring and effective data analysis are important to leak detection and localization in pipelines. Thus, an effective technique for leak detection and localization is presented in this study. The proposed scheme has four main steps. First, the learning autoregressive technique is selected to approximate the flow signal under normal conditions and extract the mathematical state-space formulation with uncertainty estimations using a combination of robust autoregressive and …support vector regression techniques. In the next step, the intelligence-based learning observer is designed using a combination of the robust learning backstepping method and a fuzzy-based technique. The learning backstepping algorithm is the main part of the algorithm that determines the leak estimation. After estimating the signals, in the third step, their classification is performed by the support vector machine algorithm. Finally, to find the size and position of the leak, the multivariable backstepping algorithm is recommended. The effectiveness of the proposed learning control algorithm is analyzed using both experimental and simulation setups. Show more

Keywords: Pipeline, fuzzy logic, autoregressive algorithm, support vector regression, backstepping observer, support vector machine, learning backstepping observer, multivariable backstepping algorithm, leak detection, leak size classification, leak localization

DOI: 10.3233/JIFS-219197

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 377-388, 2022

Authors: Demircan, Murat Levent | Acarbay, Algı

Article Type: Research Article

Abstract: Payment is an important part of people’s daily lives, and although both online and offline transactions made by credit cards increase every day with the growing interest in e-commerce, 85–90% of worldwide payment transactions are still made by cash. However, the banks, giant payment institutions like Visa and MasterCard, and Payment Service Provider companies aim to increase the number of card transactions and enhance their platforms by supporting a wide range of channels with digital solutions, enhancing the security and providing value-added services. Having the user-friendly and secure payment platforms, and easy and quick integration opportunities with the merchants are …quite critical for the banks; which shift them to outsource Virtual Point of Sale platform and focus on their core business. In this article, the vendor selection process of a bank is researched and Evaluation based on Distance to Average Solution (EDAS) method is used for vendor selection. Show more

Keywords: Multiple criteria decision making, neutrosophic fuzzy EDAS method, fuzzy Systems, software development

DOI: 10.3233/JIFS-219198

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 389-400, 2022

Authors: Oztaysi, Basar | Onar, Sezi Cevik | Kahraman, Cengiz

Article Type: Research Article

Abstract: The REGIME method is an easy to understand techniques which is based on pairwise comparisons and which can use qualitative data for decision making problems. The steps of the technique are simple and can be easily adopted to complex decision problems. Classical REGIME techniques use crisp numbers to evaluate qualitative evaluations. In this paper we propose Pythagorean Fuzzy REGIME (PF-REGIME) techniques which integrates Pythagorean Fuzzy Sets with REGIME technique. The proposed PF-REGIME is applied to waste disposal site selection problem. The decision model is constructed for three alternatives and five criteria in order to demonstrate the performance of the proposed …PF-REGIME method. Show more

Keywords: Waste disposal, pythagorean fuzzy sets, REGIME Method

DOI: 10.3233/JIFS-219199

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 401-410, 2022

Authors: Bezdan, Timea | Zivkovic, Miodrag | Bacanin, Nebojsa | Strumberger, Ivana | Tuba, Eva | Tuba, Milan

Article Type: Research Article

Abstract: Cloud computing represents relatively new paradigm of utilizing remote computing resources and is becoming increasingly important and popular technology, that supports on-demand (as needed) resource provisioning and releasing in almost real-time. Task scheduling has a crucial role in cloud computing and it represents one of the most challenging issues from this domain. Therefore, to establish more efficient resource employment, an effective and robust task allocation (scheduling) method is required. By using an efficient task scheduling algorithm, the overall performance and service quality, as well as end-users experience can be improved. As the number of tasks increases, the problem complexity rises …as well, which results in a huge search space. This kind of problem belongs to the class of NP-hard optimization challenges. The objective of this paper is to propose an approach that is able to find approximate (near-optimal) solution for multi-objective task scheduling problem in cloud environment, and at the same time to reduce the search time. In the proposed manuscript, we present a swarm-intelligence based approach, the hybridized bat algorithm, for multi-objective task scheduling. We conducted experiments on the CloudSim toolkit using standard parallel workloads and synthetic workloads. The obtained results are compared to other similar, metaheuristic-based techniques that were evaluated under the same conditions. Simulation results prove great potential of our proposed approach in this domain. Show more

Keywords: Cloud computing, task scheduling, multi-objective optimization, bat algorithm, hybridization

DOI: 10.3233/JIFS-219200

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 411-423, 2022

Authors: Omerali, Mete | Kaya, Tolga

Article Type: Research Article

Abstract: Digitalization is the key trend of the Industry 4.0 revolution. Industrial companies are transforming the way they design and maintain their products and solutions. The user requirements become more demanding. Competition among the manufacturing companies is at its limits and transforms the products to be more complex. Yet, other challenges such as faster time to market, higher quality requirements and legislation force enterprises to provide new ways of design, manufacture and service their end products. Product Lifecycle Management (PLM) is a key solution to track the entire lifespan of the product from idea to design, design to manufacture and manufacture …to service. Besides the complexity of products and production, the selection of the right PLM solution which will become the backbone of enterprises is an open problem. In this paper, a thorough literature review is conducted to analyze the most important features for selecting the right PLM solution for manufacturing firms. Moreover, to overcome the challenge of decision makers’ (DM) subjective judgments, a novel interval value spherical fuzzy COPRAS (IVSF-COPRAS) multi-criteria decision making (MCDM) method is introduced. The paper aims to help enterprises rapidly identify the best alternative vendor/solution to be selected based on the need of the organization. In order to show the applicability, DM inputs are collected from a leading defense company where the PLM selection process is ongoing. The industrial case study is provided to demonstrate the success of the proposed selection framework. Show more

Keywords: Digitalization, industry 4.0, product lifecycle management (PLM), multi-criteria decision making (MCDM), IVSF-COPRAS

DOI: 10.3233/JIFS-219201

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 425-438, 2022

Authors: Baysal, M. Emin | Sarucan, Ahmet | Büyüközkan, Kadir | Engin, Orhan

Article Type: Research Article

Abstract: The distributed permutation flow shop scheduling (DPFSS) is a permutation flow shop scheduling problem including the multi-factory environment. The processing times of the jobs in a real life scheduling problem cannot be precisely know because of the human factor. In this study, the process times and due dates of the jobs are considered triangular and trapezoidal fuzzy numbers for DPFSS environment. An artificial bee colony (ABC) algorithm is developed to solve the multi-objective distributed fuzzy permutation flow shop (DFPFS) problem. First, the proposed ABC algorithm is calibrated with the well-known DPFSS instances in the literature. Then, the DPFSS instances are …fuzzified and solved with the algorithm. According to the results, the proposed ABC algorithm performs well to solve the DFPFS problems. Show more

Keywords: Distributed fuzzy permutation flow-shop, artificial bee colony, multi-objective, fuzzy completion time, agreement index

DOI: 10.3233/JIFS-219202

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 439-449, 2022

Authors: Engin, Orhan | Yılmaz, Mustafa Kerim

Article Type: Research Article

Abstract: In the conventional scheduling problem, the parameters such as the processing time for each job and due dates are usually assumed to be known exactly, but in many real-world applications, these parameters may very dynamically due to human factors or operating faults. During the last decade, several works on scheduling problems have used a fuzzy approach including either uncertain or imprecise data. A fuzzy logic based tool for multi-objective Hybrid Flow-shop Scheduling with Multi-processor Tasks (HFSMT) problem is presented in this paper. In this study, HFSMT problems with a fuzzy processing time and a fuzzy due date are formulated, taking …Oğuz and Ercan’s benchmark problems in the literature into account. Fuzzy HFSMT problems are formulated by three-objectives: the first is to maximize the minimum agreement index and the second is to maximize the average agreement index, and the third is to minimize the maximum fuzzy completion time. An efficient genetic algorithm(GA) is proposed to solve the formulated fuzzy HFSMT problems. The feasibility and effectiveness of the proposed method are demonstrated by comparing it with the simulated annealing (SA) algorithm in the literature. Show more

Keywords: Hybrid flow shop scheduling, multi-processor tasks problems, fuzzy processing time, fuzzy due date, efficient genetic algorithm, simulated annealing

DOI: 10.3233/JIFS-219203

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 451-463, 2022

Authors: Bayturk, Engin | Esnaf, Sakir | Kucukdeniz, Tarik

Article Type: Research Article

Abstract: Facility location selection is a vital decision for companies that affects both cost and delivery time over the years. However, determination of the facility location is a NP-hard problem. A hybrid algorithm that combines revised weighted fuzzy c-means with Nelder Mead (RWFCM-NM) performs well when compared with well-known algorithms for the facility location problem (FLP) with deterministic customer demands and positions. The motivation of the study is both analyzing performance of the RWFCM-NM algorithm with probabilistic customer demands and positions and proposing a new approach for this problem. This paper develops two new algorithms for FLP when customer demands and …positions are probabilistic. The proposed algorithms are a probabilistic fuzzy c-means algorithm and Nelder-Mead (Probabilistic FCM-NM), a probabilistic revised weighted fuzzy c-means algorithm and Nelder Mead (Probabilistic RWFCM-NM) for the un-capacitated planar multi-facility location problem when customer positions and customer demands are probabilistic with predetermined service level. Proposed algorithms performances were tested with 13 data sets and comparisons were made with four well known algorithms. According to the experimental results, probabilistic RWFCM-NM algorithm demonstrates superiority on compared algorithms in terms of total transportation costs. Show more

Keywords: Multi-facility location problem, Nelder-Mead, probabilistic fuzzy c-means, probabilistic demand and position

DOI: 10.3233/JIFS-219204

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 465-475, 2022

Authors: Haktanır, Elif | Kahraman, Cengiz

Article Type: Research Article

Abstract: Process capability analysis (PCA) is a tool for measuring a process’s ability to meet specification limits (SLs), which the customers define. Process capability indices (PCIs) are used for establishing a relationship between SLs and the considered process’s ability to meet these limits as an index. PCA compares the output of a process with the SLs through these capability indices. If the customers’ needs contain vague or imprecise terms, the classical methods are inadequate to solve the problem. In such cases, the information can be processed by the fuzzy set theory. Recently, ordinary fuzzy sets have been extended to several new …types of fuzzy sets such as intuitionistic fuzzy sets, Pythagorean fuzzy sets, picture fuzzy sets, and spherical fuzzy sets. In this paper, a new extension of intuitionistic fuzzy sets, which is called penthagorean fuzzy sets, is proposed, and penthagorean fuzzy PCIs are developed. The design of production processes for COVID-19 has gained tremendous importance today. Surgical mask production and design have been chosen as the application area of the penthagorean fuzzy PCIs developed in this paper. PCA of the two machines used in surgical mask production has been handled under the penthagorean fuzzy environment. Show more

Keywords: Process capability analysis, process capability indices, penthagorean fuzzy sets, surgical mask, COVID-19

DOI: 10.3233/JIFS-219205

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 477-489, 2022

Authors: Tunc, Ali | Tasdemir, Sakir | Koklu, Murat | Cinar, Ahmet Cevahir

Article Type: Research Article

Abstract: Biometry is the science that enables living things to be distinguished by examining their physical and behavioral characteristics. The facial recognition system (FCS) is a kind of biometric system. FCS provides a unique mathematical model by determining the distance between the cheekbones, chin, nose, eyes, jawline, and similar positions using the facial features of the persons. Determining the gender and age group of chosen persons’ from face images is the main purpose of this study. It is targeted to distinguish the gender of the person and to obtain information about the person is children or adults by making essential works …on the images. Convolutional neural network (CNN) is one of the deep face recognition algorithms that widely used to recognize facial images. This study is suggested as a study that detects noise in images using the fuzzy logic-based filter method and classifies this cleared data by gender using the matrix completion and CNN. TensorFlow which is a machine learning library that used to train and tests deep learning methods is used for experiments. The customer photographs taken during using the system are transformed into a matrix expression through a system trained using this algorithm. The obtained results indicated that the offered technique detects age and gender with a 96% accuracy value and 1.145 seconds time. Show more

Keywords: Age classification, convolutional neural network, deep learning, fuzzy logic, gender classification

DOI: 10.3233/JIFS-219206

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 491-501, 2022

Authors: Namlı, Özge H. | Yanık, Seda | Nouri, Faranak | Serap Şengör, N. | Koyuncu, Yusuf Mertkan | Uçar, Ömer Berk

Article Type: Research Article

Abstract: In today’s competitive business environment, companies are striving to reduce costs and workload of call centers while improving customer satisfaction. In this study, a framework is presented that predicts and encourages taking proactive actions to solve customer problems before they lead to a call to the call center. Machine learning techniques are implemented and models are trained with a dataset which is collected from an internet service provider’s systems in order to detect internet connection problems of the customers proactively. Firstly, two classification techniques which are multi perceptron neural networks and radial basis neural networks are applied as supervised techniques …to classify whether the internet connection of customers is problematic or not. Then, by using unsupervised techniques, namely Kohonnen’s neural networks and Adaptive Resonance Theory neural networks, the same data set is clustered and the clusters are used for the customer problem prediction. The methods are then integrated with an ensemble technique bagging. Each method is implemented with bagging in order to obtain improvement on the estimation error and variation of the accuracy. Finally, the results of the methods applied for classification and clustering with and without bagging are evaluated with performance measures such as recall, accuracy and Davies-Bouldin index, respectively. Show more

Keywords: Call center problem prediction, classification, clustering, artificial neural networks, bagging

DOI: 10.3233/JIFS-219207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 503-515, 2022

Authors: Cinar, Ulas | Cebi, Selcuk

Article Type: Research Article

Abstract: Risk management is the key factor to obtain safety in the working environment and its effectiveness increases with accuracy assessment and robust analysis. However, it is hard to succeed because of uncertainties in the working environment. Therefore, there are a lot of risk assessment methods in the literature to assess occupational health and safety risks. The traditional risk assessment methods handle each activity in the working environment separately and they do not consider the interactions among them. Furthermore, in these methods, potential outcomes of the risk parameters are considered based on the most possible outcome although there may be more …than one potential outcome. Differ from the traditional methods, The House of Safety method has been proposed to consider all potential outcomes and handle the interactions among the activities. In this study, an extension of The House of Safety is proposed to consider interactions among potential risks and to determine the most effective prevention method based on the potential risks. Hence, this extension provides an evaluation of the whole system. The proposed model has been developed by integrating Fuzzy Inference System (FIS), Fuzzy Analytical Hierarchy Process (FAHP), and DEMATEL into Quality Function Deployment (QFD). In this direction, FIS is used to determine activity-related probabilities, “FAHP” is utilized to identify all possible damage potentials of risks, and the DEMATEL is used to clarify interactions among risks. Finally, all information produced by these methods were aggregated to obtain total risk scores by using QFD. In addition, a second home has been created to link prevention and risks. Therefore, an effective prevention plan has been made to eliminate priority risks with all effective parameters. This stage provides the opportunity for optimum prevention plan against risk or risk groups dominating the system at the same time. In this study, unlike traditional methods including a partial risk assessment perspective, an integrated method that takes into account the risks on their own and the interactions between them is proposed in the literature, and the proposed approach has been applied to an open pit mine. Show more

Keywords: The house of safety, risk assessment method, occupational safety, fuzzy inference system, fuzzy AHP, DEMATEL, QFD

DOI: 10.3233/JIFS-219208

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 517-528, 2022

Authors: Aydın, Serhat | Yörükoğlu, Mehmet | Kabak, Mehmet

Article Type: Research Article

Abstract: The fourth party logistics (4PL) is an combiner that designs and implements the holistic supply chain solutions by using skills, knowledge, technology and resources of the service provider and its customer. A 4PL provider is also a technological service provider with eligible intellectual capital and the sufficient computer/software infrastructure. Defining the most appropriate 4PL service provider from the alternatives is not easy for companies, the solution can be addressed within the framework of the Multi-Criteria Decision Making (MCDM) problem, and subjective and uncertain data are required for this solution. “Fuzzy set theory” is a helpful tool for dealing with such …subjectivity and uncertainty. In recent times, extensions of fuzzy sets have been evolved to address and describe the subjectivities and uncertainties more widely. Neutrosophic sets are one of the extensions of fuzzy sets, and unlike other extensions, they use the independent indeterminacy-membership function, thereby extracting important information and improving the accuracy of the decision-making process. A neutronophic MCDM method was proposed for the assessment of 4PL providers’ performance. In the application part of the study, neutrosophic language scale was used by three experts to evaluate the performance of 4PL providers. Then the closeness coefficient of each alternative was computed and sequenced in descending order. We also presented a comparative analysis with neutrosphic TOPSIS method. The results determined that the proposed neutrosophic MCDM method could be used in the performance evaluation of 4PL providers and similar problems. Show more

Keywords: Supply chain management, 4PLs, multi criteria decision making, neutrosophic sets

DOI: 10.3233/JIFS-219209

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 529-539, 2022

Authors: Seker, Sukran

Article Type: Research Article

Abstract: The glass manufacturing includes operations, such as batch forming using raw materials, melting, forming, annealing, quality check and package. Due to risky processes in glass manufacturing, significant health hazards for workers are present in the glass industry. Risk assessment is effective way to prevent accidents and protect workers from serious accidents during glass manufacturing. To assess health hazards associated with glass manufacturing, in this study Risk Matrix and The Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method are integrated under Interval-Valued Intuitionistic Fuzzy (IVIF) environment to prioritize risk factors and suggest required preventive and protective measures. …Suggested preventive and protective measures provide technical, economic and environmental challenges for glass manufacturing firms. Once the importance weight of risk parameters in Risk Matrix’ are determined, the risk factors are assessed by performing IVIF-TOPSIS method during glass manufacturing. In order to verify the validity and stability of the proposed risk assessment model, sensitivity and comparative analysis are accomplished at the end of the study. Show more

Keywords: Risk assessment, uncertainty, risk matrix, IVIF-TOPSIS

DOI: 10.3233/JIFS-219210

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 541-550, 2022

Authors: Rashid, Tabasam | Sarwar Sindhu, M.

Article Type: Research Article

Abstract: Motivated by interval-valued hesitant fuzzy sets (IVHFSs) and picture fuzzy sets (P c FSs), a notion of interval-valued hesitant picture fuzzy sets (IVHP c FSs) is presented in this article. The concept of IVHP c FSs is put forward and some operational rules are developed to deal with it. The cosine similarity measures (SMs) are modified for IVHP c FSs to deal with interval-valued hesitant picture fuzzy (IVHP c F) data and the linear programming (LP) methodology is used to find out the criteria’s weights. A multiple criteria decision making (MCDM) approach is then developed …to tackle the vague and ambiguous information involved in MCDM problems under the framework of IVHP c FSs. For the validation and strengthen of the proposed MCDM approach a practical example is put forward to select the educational expert at the end. Show more

Keywords: Fuzzy sets, picture fuzzy sets, hesitant fuzzy sets, IVHFSs, LP technique

DOI: 10.3233/JIFS-219211

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 551-561, 2022

Authors: Traneva, Velichka | Tranev, Stoyan

Article Type: Research Article

Abstract: Analysis of variance (ANOVA) is an important method in data analysis, which was developed by Fisher. There are situations when there is impreciseness in data In order to analyze such data, the aim of this paper is to introduce for the first time an intuitionistic fuzzy two-factor ANOVA (2-D IFANOVA) without replication as an extension of the classical ANOVA and the one-way IFANOVA for a case where the data are intuitionistic fuzzy rather than real numbers. The proposed approach employs the apparatus of intuitionistic fuzzy sets (IFSs) and index matrices (IMs). The paper also analyzes a unique set of data …on daily ticket sales for a year in a multiplex of Cinema City Bulgaria, part of Cineworld PLC Group, applying the two-factor ANOVA and the proposed 2-D IFANOVA to study the influence of “ season ” and “ ticket price ” factors. A comparative analysis of the results, obtained after the application of ANOVA and 2-D IFANOVA over the real data set, is also presented. Show more

Keywords: Decision making, index matrix, intuitionistic fuzzy sets, variation analysis

DOI: 10.3233/JIFS-219212

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 563-573, 2022

Authors: Tuncalı Yaman, Tutku | Bilgiç, Emrah | Fevzi Esen, M.

Article Type: Research Article

Abstract: Injury severity in motor vehicle traffic accidents is determined by a number of factors including driver, vehicle, and environment. Airbag deployment, vehicle speed, manner of collusion, atmospheric and light conditions, degree of ejection of occupant’s body from the crash, the use of equipment or other forces to re-move occupants from the vehicle, model and type of vehicle have been considered as important risk factors affecting accident severity as well as driver-related conditions such as age, gender, seatbelt use, alcohol and drug involvement. In this study, we aim to identify important variables that contribute to injury severity in the traffic crashes. …A contemporary dataset is obtained from National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS). To identify accident severity groups, we performed different clustering algorithms including fuzzy clustering. We then assessed the important factors affecting injury severity by using classification and regression trees (CRT). The results which would guide car manufacturers, policy makers and insurance companies indicate that the most important factor in defining injury severity is deployment of air-bag, followed by extrication, ejection occurrences, and travel speed and alcohol involvement. Show more

Keywords: Traffic accidents, fuzzy clustering, data mining, injury severity, clustering, CRT

DOI: 10.3233/JIFS-219213

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 575-592, 2022

Authors: Unal, Yagmur | Temur, Gul T.

Article Type: Research Article

Abstract: In today’s highly competitive business market, the issue of sustainable supplier selection attracts great attention due to increased awareness of both social and environmental issues. The power of companies in the supply chain is determined not only by their own performance, but also by the power of other actors in the chain. As a field of study, the selection of sustainable suppliers remains its popularity because it requires developing a systematic procedure that addresses conflicting quantifiable and non-quantifiable factors simultaneously. In this study, one of the advanced fuzzy approaches called Spherical Fuzzy Sets (SFS) has been used to prioritize criteria …that affect sustainable supplier selection. The proposed methodology combines the Spherical Fuzzy Sets and the analytic hierarchy process (AHP) and takes into account four main criteria: economic, quality, social and environmental criteria. In order to prioritize the main and sub criteria, questionnaires were conducted with three experts who have valuable experience in this field of study. After then, for the selection of the best sustainable supplier, a real selection problem in an international company was handled. The figured out ranking of the criteria and supplier alternatives can be used as a guide by the researchers and industrial experts who are responsible for sustainable supplier selection. To measure how much unit increase in weights assigned to key criteria affects supplier selection, a sensitivity analysis was carried out. It was noticed that the selection procedure for the selected company is not highly sensitive to changes. Show more

Keywords: Analytic hierarchy process (AHP), spherical fuzzy sets, sustainable supplier selection

DOI: 10.3233/JIFS-219214

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 593-603, 2022

Authors: Ilbahar, Esra | Cebi, Selcuk | Kahraman, Cengiz

Article Type: Research Article

Abstract: Both national and international encouragements for research and development (R&D) projects have been growing worldwide. Since R&D projects include various uncertainties related to time, technology, finance, and knowledge, risk management studies are highly significant for the success of these projects. In risk management, all of the potential actions that might have negative impacts on the processes or outputs of a project should be determined, and if it is possible, their negative impacts should be reduced before the project starts. In this study, after risks in R&D projects are determined, the alternative projects are prioritized with respect to these risks by …using an approach based on interval-valued intuitionistic fuzzy AHP and fuzzy information axiom. Interval-valued Intuitionistic Fuzzy Analytic Hierarchy Process (IVIF AHP) is used to determine the importance degrees of the determined risk factors while fuzzy information axiom is used to evaluate R&D projects considering these risk factors. It is revealed that the most important risk is “Abnormal changes in cost” while the least important one is “Deficiencies in contract articles”. Show more

Keywords: R&D, risk assessment, intuitionistic fuzzy sets, AHP, fuzzy information axiom

DOI: 10.3233/JIFS-219215

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 605-614, 2022