Pub Date : 2023-08-17DOI: 10.2174/2666294902666230817162030
M. Nadeem, Masood Ahmad, Syed Anas Ansar, Prabhash Chandra Pathak, Rajeev Kumar, R. Khan
Quantum computer development attracts the security experts of software. The rapid development of number of qubit in quantum computer makes the present security mechanism of software insecure. Software developers need to pay attention to the development of quantum computers in terms of software security. Software security evaluation focuses on the fundamental security features of software as well as the quantum enable security alternatives. The software security evaluation is the most crucial part of surveying, controlling, and administering security in order to further improve the properties of safety. It's crucial to understand that performing a security assessment early on in the develop-ment process can help you find bugs, vulnerabilities, faults, and attacks. In this quantitative study, the definition and use of the quantum computing security approach in software security will be cov-ered. The cryptographic calculations had to secure our institutions based on computers and networks. The Fuzzy Technique for Order Preference by Similarity to Ideal Situation (Fuzzy-TOPSIS) to quantitatively assess the rank of the quantum enable security alternatives with security factors. The Quantum Key Distribution [A2], the quantum technique of security approach, has got the top priority and quantum key distribution in GHz state [A6] got the least in the estimation of software security during the era of quantum computer by the neural network method of Fuzzy-TOPSIS. The quantum mechanism of computing makes classical computing insecure. The secu-rity estimation of software makes developers focus on the quantum mechanism of security. The quantum mechanism of quantum key distribution is to make software secure.
{"title":"Security Evaluation of Software by Using Fuzzy-TOPSIS through Quantum Criteria","authors":"M. Nadeem, Masood Ahmad, Syed Anas Ansar, Prabhash Chandra Pathak, Rajeev Kumar, R. Khan","doi":"10.2174/2666294902666230817162030","DOIUrl":"https://doi.org/10.2174/2666294902666230817162030","url":null,"abstract":"\u0000\u0000Quantum computer development attracts the security experts of software. The rapid development of number of qubit in quantum computer makes the present security mechanism of software insecure. Software developers need to pay attention to the development of quantum computers in terms of software security.\u0000\u0000\u0000\u0000Software security evaluation focuses on the fundamental security features of software as well as the quantum enable security alternatives. The software security evaluation is the most crucial part of surveying, controlling, and administering security in order to further improve the properties of safety.\u0000\u0000\u0000\u0000It's crucial to understand that performing a security assessment early on in the develop-ment process can help you find bugs, vulnerabilities, faults, and attacks. In this quantitative study, the definition and use of the quantum computing security approach in software security will be cov-ered. The cryptographic calculations had to secure our institutions based on computers and networks.\u0000\u0000\u0000\u0000The Fuzzy Technique for Order Preference by Similarity to Ideal Situation (Fuzzy-TOPSIS) to quantitatively assess the rank of the quantum enable security alternatives with security factors.\u0000\u0000\u0000\u0000The Quantum Key Distribution [A2], the quantum technique of security approach, has got the top priority and quantum key distribution in GHz state [A6] got the least in the estimation of software security during the era of quantum computer by the neural network method of Fuzzy-TOPSIS.\u0000\u0000\u0000\u0000The quantum mechanism of computing makes classical computing insecure. The secu-rity estimation of software makes developers focus on the quantum mechanism of security. The quantum mechanism of quantum key distribution is to make software secure.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131972830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-20DOI: 10.2174/2666294901666220820180818
S. Kumar De, Kousik Bhattacharya, Biswajit Roy
This article deals with a new decision-making process under neutrosophic fuzzy environment. First of all, we develop various types of neutrosophic set by means of neutrosophic cones. In fact, this set has been developed from the general equation of second degree in the field of classical geometry. Considering the neutrosophic components “true membership”, the “falsity membership” and the “indeterminacy” as the three variables of a three-dimensional rectangular axes we develop various type of cones like structures of the traditional neutrosophic set and hence a new defuzzification method. Fuzzy set has some limitations in its domain [0,1] to describe the real-life decision-making problems. The problem of difficulties lies on the variation of lower and upper bound and also the single valued logic (membership function only) systems. In reality, three valued logics (membership function, non-membership function and indeterminacy) has been established in the name of Neutrosophic logic/ sets, two valued logics (membership and non-membership functions) has developed in the name of Intuitionistic fuzzy logic/sets. In three valued logic system, the concepts of negation are now a growing subject of any group decision making problems. However, to draw a clear estimation over a neutrosophic decision has not yet been studied by the modern researchers. Various kinds of new establishments of the Neutrosophic set has been studued in the algebraic point of view along with some polynomial structures. We have seen that; no finite geometric structures have been developed yet to qualify the real-world problems. We consider the three components of a neutrosophic set as the variables of three-dimensional geometry. Since, the decisions are compact and constructive so, we may consider the convex neutrosophic cone for analyzing single/ multiple group decision making problems. Various definitions are made over the cone- fundamentals using non-standard neutrosophic set in the domain [-1,1]×[-1,1]×[-1,1] . Then, we have studied the constructions of several expressions / functions of neutrosophic cones such as reciprocal cone, enveloping cone via novel thinking process. Then using some examples, we have developed a new ranking method along with their geometric structures exclusively. In this changing world, the nature of decision-making behaviors is also changing rapidly. So, the need of establishing new concepts is an emerging area of research. However, more attentions are to be paid in discussing such vital issues in near future. The proposed approach may be applied for the decision -making problems of global issues also.
{"title":"Application of Fuzzy Neutrosophic Cone in Decision Making","authors":"S. Kumar De, Kousik Bhattacharya, Biswajit Roy","doi":"10.2174/2666294901666220820180818","DOIUrl":"https://doi.org/10.2174/2666294901666220820180818","url":null,"abstract":"\u0000\u0000This article deals with a new decision-making process under neutrosophic fuzzy environment. First of all, we develop various types of neutrosophic set by means of neutrosophic cones. In fact, this set has been developed from the general equation of second degree in the field of classical geometry. Considering the neutrosophic components “true membership”, the “falsity membership” and the “indeterminacy” as the three variables of a three-dimensional rectangular axes we develop various type of cones like structures of the traditional neutrosophic set and hence a new defuzzification method.\u0000\u0000\u0000\u0000Fuzzy set has some limitations in its domain [0,1] to describe the real-life decision-making problems. The problem of difficulties lies on the variation of lower and upper bound and also the single valued logic (membership function only) systems. In reality, three valued logics (membership function, non-membership function and indeterminacy) has been established in the name of Neutrosophic logic/ sets, two valued logics (membership and non-membership functions) has developed in the name of Intuitionistic fuzzy logic/sets. In three valued logic system, the concepts of negation are now a growing subject of any group decision making problems. However, to draw a clear estimation over a neutrosophic decision has not yet been studied by the modern researchers.\u0000\u0000\u0000\u0000Various kinds of new establishments of the Neutrosophic set has been studued in the algebraic point of view along with some polynomial structures. We have seen that; no finite geometric structures have been developed yet to qualify the real-world problems.\u0000\u0000\u0000\u0000We consider the three components of a neutrosophic set as the variables of three-dimensional geometry. Since, the decisions are compact and constructive so, we may consider the convex neutrosophic cone for analyzing single/ multiple group decision making problems.\u0000\u0000\u0000\u0000Various definitions are made over the cone- fundamentals using non-standard neutrosophic set in the domain [-1,1]×[-1,1]×[-1,1] . Then, we have studied the constructions of several expressions / functions of neutrosophic cones such as reciprocal cone, enveloping cone via novel thinking process. Then using some examples, we have developed a new ranking method along with their geometric structures exclusively.\u0000\u0000\u0000\u0000In this changing world, the nature of decision-making behaviors is also changing rapidly. So, the need of establishing new concepts is an emerging area of research. However, more attentions are to be paid in discussing such vital issues in near future.\u0000\u0000\u0000\u0000The proposed approach may be applied for the decision -making problems of global issues also.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121594559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-21DOI: 10.2174/2666294901666220621105325
Duygu Sergi, I. Sari
Retail management has evolved into a new business model with the development of online shopping habits. There may be significant differences between onsite service and online service in terms of customer expectations. In this study, companies providing online grocery services in Turkey are evaluated by examining the services they provide from the perspective of customers. Fuzzy Z numbers, which also add the reliability of linguistic assessments to the analysis, are used in order to better describe the uncertainty. Fuzzy Z-analytic hierarchy method (FZ-AHP) is used to weight the decision criteria, and fuzzy Z-Grey relational analysis (FZ-GRA) method is used to find the best online market company. As a result of the analysis, it is revealed that the most important criteria for online grocery shopping are minimum order amount and brand diversity. The results are also compared with ordinary fuzzy methods. The comparison of the methods used in the study shows that although the ranks of the criteria and alternatives are the same, using fuzzy Z linguistic scale results in a wider interval for the weights and the scores of the alternatives which could change the ordering, especially in cases where criterion weights or alternative scores are very close to each other.
{"title":"Evaluation of Online Grocery Platform Alternatives Using Fuzzy Z-Numbers","authors":"Duygu Sergi, I. Sari","doi":"10.2174/2666294901666220621105325","DOIUrl":"https://doi.org/10.2174/2666294901666220621105325","url":null,"abstract":"\u0000\u0000Retail management has evolved into a new business model with the development of online shopping habits. There may be significant differences between onsite service and online service in terms of customer expectations.\u0000\u0000\u0000\u0000In this study, companies providing online grocery services in Turkey are evaluated by examining the services they provide from the perspective of customers. Fuzzy Z numbers, which also add the reliability of linguistic assessments to the analysis, are used in order to better describe the uncertainty.\u0000\u0000\u0000\u0000Fuzzy Z-analytic hierarchy method (FZ-AHP) is used to weight the decision criteria, and fuzzy Z-Grey relational analysis (FZ-GRA) method is used to find the best online market company.\u0000\u0000\u0000\u0000As a result of the analysis, it is revealed that the most important criteria for online grocery shopping are minimum order amount and brand diversity. The results are also compared with ordinary fuzzy methods.\u0000\u0000\u0000\u0000The comparison of the methods used in the study shows that although the ranks of the criteria and alternatives are the same, using fuzzy Z linguistic scale results in a wider interval for the weights and the scores of the alternatives which could change the ordering, especially in cases where criterion weights or alternative scores are very close to each other.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129855496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-10DOI: 10.2174/2666294901666220610143613
Maria N. Rapti, Basil K. Papadopoulos
In this article, we develop new constructed methods with specific conditions. The first method is a generalization of convex combination using n fuzzy implications. The second method is a parameterization of Lukasiewicz implication in an Ordering Property (OP) fuzzy implication form. The innovation in this work is the presentation of three new constructed methods of (OP) polynomial and (OP) rational fuzzy implications. We investigate some families of Ordering Property (OP) and Ordering Property (OP) Rational fuzzy implications. To these methods, we give some coefficient conditions in order to satisfy basic properties like ordering property (OP), identity property (IP) and contrapositive symmetry (CP). Fuzzy implication functions are one of the main operations in fuzzy logic. They generalize the classical implication, which takes values in the set {0,1}, to fuzzy logic, where the truth values belong to the unit interval [0,1]. The study of this class of operations has been extensively developed in the literature in the last 30 years from both theoretical and applicational points of view. In this paper, we develop five new methods for constructing fuzzy implications with specific properties. The paper starts by presenting the first fuzzy implication construction machine that uses n fuzzy implications with specific conditions. Next, we parameterize Lukasiewicz implication and create new families of (OP) polynomial and (OP) rational implications. For each method we investigate which conditions are satisfied and we give some examples. The first constructed method uses n fuzzy implications in a linear product representation. The second method is an (OP) polynomial implication a parameterized Lukasiewicz implication. The third method is a rational implication with five parameters. In the fourth method we give a general form in the previous method by changing variables x and y with increasing functions. Finally, the last method is another (OP) rational implication with three parameters. In each method we present the properties that are satisfied. We generalize the (OP) polynomial and rational by replacing the variables with monotonic functions or add powers on them. Finally, we generalize and we give examples of new produced fuzzy implications. As a future work, we can create new families of rational implications by changing the polynomials of the numerator and denominator so that they satisfy more properties. Finally, the new methods we presented can contribute in the construction of uninorms and copulas under certain conditions.
{"title":"A Novel Construction Method of (OP) Polynomial and Rational Fuzzy Implications","authors":"Maria N. Rapti, Basil K. Papadopoulos","doi":"10.2174/2666294901666220610143613","DOIUrl":"https://doi.org/10.2174/2666294901666220610143613","url":null,"abstract":"\u0000\u0000In this article, we develop new constructed methods with specific conditions. The first method is a generalization of convex combination using n fuzzy implications. The second method is a parameterization of Lukasiewicz implication in an Ordering Property (OP) fuzzy implication form. The innovation in this work is the presentation of three new constructed methods of (OP) polynomial and (OP) rational fuzzy implications. We investigate some families of Ordering Property (OP) and Ordering Property (OP) Rational fuzzy implications. To these methods, we give some coefficient conditions in order to satisfy basic properties like ordering property (OP), identity property (IP) and contrapositive symmetry (CP).\u0000\u0000\u0000\u0000Fuzzy implication functions are one of the main operations in fuzzy logic. They generalize the classical implication, which takes values in the set {0,1}, to fuzzy logic, where the truth values belong to the unit interval [0,1]. The study of this class of operations has been extensively developed in the literature in the last 30 years from both theoretical and applicational points of view.\u0000\u0000\u0000\u0000In this paper, we develop five new methods for constructing fuzzy implications with specific properties. The paper starts by presenting the first fuzzy implication construction machine that uses n fuzzy implications with specific conditions. Next, we parameterize Lukasiewicz implication and create new families of (OP) polynomial and (OP) rational implications. For each method we investigate which conditions are satisfied and we give some examples.\u0000\u0000\u0000\u0000The first constructed method uses n fuzzy implications in a linear product representation. The second method is an (OP) polynomial implication a parameterized Lukasiewicz implication. The third method is a rational implication with five parameters. In the fourth method we give a general form in the previous method by changing variables x and y with increasing functions. Finally, the last method is another (OP) rational implication with three parameters.\u0000\u0000\u0000\u0000In each method we present the properties that are satisfied. We generalize the (OP) polynomial and rational by replacing the variables with monotonic functions or add powers on them. Finally, we generalize and we give examples of new produced fuzzy implications.\u0000\u0000\u0000\u0000As a future work, we can create new families of rational implications by changing the polynomials of the numerator and denominator so that they satisfy more properties. Finally, the new methods we presented can contribute in the construction of uninorms and copulas under certain conditions.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117117970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-12DOI: 10.2174/2666294901666220512124732
A. Sarucan, Aysel Söğüt, M. E. Baysal
In this study, the integrated methods Hesitant Fuzzy Analytic Hierarchy Process (HF-AHP), Fuzzy COmplex Proportional Assessment (F-COPRAS) and Fuzzy Technique for Order Performance to Ideal Solution (F-TOPSIS) were used for job evaluation studies in a food company. There has been a decline in employee performance in the company. Unfair wages and unequal workload were identified as the reasons for the failure. Therefore, it has been observed that the staff turnover rate in the company is quite high. The objective is to determine a fair wage policy that will increase employee satisfaction by stratifying with job evaluation analysis between positions. The experts of Human Resources Department determined eight competency evaluation criteria for job evaluation studies in the proposed approach. Based on their judgments on these criteria, the competencies were rated using a linguistic scale and the weighting values were calculated using HF-AHP method. These values are inputs for the next stage. Employees were ranked using F-COPRAS and F-TOPSIS methods. This study showed that the integrated method can be an effective alternative solution approach for calculating the weighting values and ranking of competencies in job evaluation studies. It has been shown that the use of the strata created as a result of this study is a great facilitator in determining employee pay policies.
{"title":"A Fuzzy Multi Criteria Decision Making Methodology for Job Evaluation","authors":"A. Sarucan, Aysel Söğüt, M. E. Baysal","doi":"10.2174/2666294901666220512124732","DOIUrl":"https://doi.org/10.2174/2666294901666220512124732","url":null,"abstract":"\u0000\u0000In this study, the integrated methods Hesitant Fuzzy Analytic Hierarchy Process (HF-AHP), Fuzzy COmplex Proportional Assessment (F-COPRAS) and Fuzzy Technique for Order Performance to Ideal Solution (F-TOPSIS) were used for job evaluation studies in a food company.\u0000\u0000\u0000\u0000There has been a decline in employee performance in the company. Unfair wages and unequal workload were identified as the reasons for the failure. Therefore, it has been observed that the staff turnover rate in the company is quite high.\u0000\u0000\u0000\u0000The objective is to determine a fair wage policy that will increase employee satisfaction by stratifying with job evaluation analysis between positions.\u0000\u0000\u0000\u0000The experts of Human Resources Department determined eight competency evaluation criteria for job evaluation studies in the proposed approach. Based on their judgments on these criteria, the competencies were rated using a linguistic scale and the weighting values were calculated using HF-AHP method. These values are inputs for the next stage. Employees were ranked using F-COPRAS and F-TOPSIS methods.\u0000\u0000\u0000\u0000This study showed that the integrated method can be an effective alternative solution approach for calculating the weighting values and ranking of competencies in job evaluation studies.\u0000\u0000\u0000\u0000It has been shown that the use of the strata created as a result of this study is a great facilitator in determining employee pay policies.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130527807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-10DOI: 10.2174/2666294901666220510095557
F. Nucci
This work studies the single vehicle routing problem (VRP) with multi-shift and fuzzy uncertainty. In this case, a company perpetually exploits a vehicle to accomplish demand over a scheduling period of several work shifts. In our problem, a crew performs maintenance jobs at different locations. The working team operates in different shifts that have a maximum duration, but recurrently returns to the depot by the end of the shift to avoid overtime. The objective is to minimize the number of shifts and the completion time (makespan). In addition, we analyze the influence of uncertainty in driving and processing times on the overtime avoidance constraint in shift duration. We develop an Artificial Immune Heuristic to determine optimal solutions considering both makespan and overtime avoidance. We implement a Pareto-based framework to evaluate the impact of uncertainty. We present several numerical case studies to examine the problem. In particular, we analyze different case study scenarios inferred from the environmental changes in travel and processing times observed in Apulia region (SE Italy) during the COVID-19 lockdown periods occurred in spring (started on March 9, 2020) and autumn (after November 6, 2020) of the year 2020. As soon as the Italian COVID-19 restrictions occurred in the spring and autumn of 2020, the work program was revised due to the changing environment. Our approach allowed for the rapid release of new robust maintenance programs. Results show significant improvements with the presented approach.
{"title":"Multi-Shift Single-Vehicle Routing Problem Under Fuzzy Uncertainty During the COVID-19 Pandemic-","authors":"F. Nucci","doi":"10.2174/2666294901666220510095557","DOIUrl":"https://doi.org/10.2174/2666294901666220510095557","url":null,"abstract":"\u0000\u0000This work studies the single vehicle routing problem (VRP) with multi-shift and fuzzy uncertainty. In this case, a company perpetually exploits a vehicle to accomplish demand over a scheduling period of several work shifts. In our problem, a crew performs maintenance jobs at different locations. The working team operates in different shifts that have a maximum duration, but recurrently returns to the depot by the end of the shift to avoid overtime.\u0000\u0000\u0000\u0000The objective is to minimize the number of shifts and the completion time (makespan). In addition, we analyze the influence of uncertainty in driving and processing times on the overtime avoidance constraint in shift duration. We develop an Artificial Immune Heuristic to determine optimal solutions considering both makespan and overtime avoidance. We implement a Pareto-based framework to evaluate the impact of uncertainty.\u0000\u0000\u0000\u0000We present several numerical case studies to examine the problem. In particular, we analyze different case study scenarios inferred from the environmental changes in travel and processing times observed in Apulia region (SE Italy) during the COVID-19 lockdown periods occurred in spring (started on March 9, 2020) and autumn (after November 6, 2020) of the year 2020.\u0000\u0000\u0000\u0000As soon as the Italian COVID-19 restrictions occurred in the spring and autumn of 2020, the work program was revised due to the changing environment. Our approach allowed for the rapid release of new robust maintenance programs. Results show significant improvements with the presented approach.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114222853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-10DOI: 10.2174/2666294901666220510102203
Fatma Yaşlı, G. T. Temur, Bersam Bolat
Tech startups are fast-growing businesses that target the demands of the marketplace by developing innovative products, services, or platforms. Startups ensure socially, economically, or environmentally more effective alternatives by using or by creating appropriate technologies. Many factors have become prominent regarding the success and sustainability of the product or service offered by the startup: investment, experience, and education of the team, leadership of the management, creativity, innovation, technological breakthroughs, surrounding community, future perspective, target marketing strategy, location and the analysis of the market, etc. But since 80% of startups do not survive after five years, defining the important risk factors is crucial to develop the right strategies for successful startups. In this study, the risk factors were defined based on the business model, which has an important place in the success of the technology startups, which use technology intensively. Comprehensive risk analysis on identified factors is presented to identify effective managerial strategies for technology startups not to fail. Spherical Fuzzy Failure Mode and Impact Analysis (SFFMEA) was used within the framework of a business model canvas for risk analysis for the failure of technology startup projects. Due to the lack of recorded data for analysis, the opinions of field experts were used. While the business model canvas guided the identification of detailed risk factors, FMEA enabled the risk analysis of factors that cause startup projects to fail, to consider parameters related to the probability of the relevant risk factors, their impact on the failure of the project, and the detection level of the risk factor. Spherical Fuzzy, on the other hand, allowed the quantitative inference of FMEA's comprehensive parameter definitions associated with the risk factors through experts. Thus, all risk factors that may cause the failure of tech startups were ranked according to their risk priority numbers (RPNs), with the SFFMEA analysis which offers a comprehensive risk analysis. The findings show that the most important causes of the tech startup’s failure are “non-compliance with existing restrictions”, “in-appropriate venture capital strategy” and “lack of clustering support”. These failure modes can be interpreted according to their frequency of encounter, potential effects, and detectability, and can be considered as an important finding in the development of appropriate managerial strategies for the mitigation of the risk factors, so as to survive in their first five years. Also, with the proposed risk analysis methodology, a comprehensive analysis of any startup project can be performed according to its conditions and characteristics.
{"title":"FMEA Method Using Spherical Fuzzy Sets for Risk Analysis of the Tech Startup","authors":"Fatma Yaşlı, G. T. Temur, Bersam Bolat","doi":"10.2174/2666294901666220510102203","DOIUrl":"https://doi.org/10.2174/2666294901666220510102203","url":null,"abstract":"\u0000\u0000Tech startups are fast-growing businesses that target the demands of the marketplace by developing innovative products, services, or platforms. Startups ensure socially, economically, or environmentally more effective alternatives by using or by creating appropriate technologies. Many factors have become prominent regarding the success and sustainability of the product or service offered by the startup: investment, experience, and education of the team, leadership of the management, creativity, innovation, technological breakthroughs, surrounding community, future perspective, target marketing strategy, location and the analysis of the market, etc. But since 80% of startups do not survive after five years, defining the important risk factors is crucial to develop the right strategies for successful startups. In this study, the risk factors were defined based on the business model, which has an important place in the success of the technology startups, which use technology intensively. Comprehensive risk analysis on identified factors is presented to identify effective managerial strategies for technology startups not to fail.\u0000\u0000\u0000\u0000Spherical Fuzzy Failure Mode and Impact Analysis (SFFMEA) was used within the framework of a business model canvas for risk analysis for the failure of technology startup projects. Due to the lack of recorded data for analysis, the opinions of field experts were used. While the business model canvas guided the identification of detailed risk factors, FMEA enabled the risk analysis of factors that cause startup projects to fail, to consider parameters related to the probability of the relevant risk factors, their impact on the failure of the project, and the detection level of the risk factor. Spherical Fuzzy, on the other hand, allowed the quantitative inference of FMEA's comprehensive parameter definitions associated with the risk factors through experts. Thus, all risk factors that may cause the failure of tech startups were ranked according to their risk priority numbers (RPNs), with the SFFMEA analysis which offers a comprehensive risk analysis.\u0000\u0000\u0000\u0000The findings show that the most important causes of the tech startup’s failure are “non-compliance with existing restrictions”, “in-appropriate venture capital strategy” and “lack of clustering support”.\u0000\u0000\u0000\u0000These failure modes can be interpreted according to their frequency of encounter, potential effects, and detectability, and can be considered as an important finding in the development of appropriate managerial strategies for the mitigation of the risk factors, so as to survive in their first five years. Also, with the proposed risk analysis methodology, a comprehensive analysis of any startup project can be performed according to its conditions and characteristics.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121664627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-28DOI: 10.2174/2666294901666220428145618
I. Kouatli, Skander Ben Abdallah, Abbas Terhini, Hiba Naccash
Real options theory allows taking into account the value of some sources of managerial flexibility and therefore assessing more accurately a project value. The positive value of flexibility results from limiting the impacts of adverse events while taking advantage of positive ones. One of the main lessons is that uncertainty adds value in the presence of flexibility. Ambiguous parameters that have a significant effect on the project value are usually represented as fuzzy sets using Zadeh’s classical theory of Fuzzy logic” (also termed as “type-1”). However, there have been so many derivatives and expansions of the fuzzy set theories developed by different researchers. This paper reviews the applicability of ROA to fuzzy sets (classical and extended) implementation to decision-making for large projects where project timing and uncertainty are key parameters affecting the project value. The objective of this review is to identify the research gap as well as provide an elementary guide of the applicability of such techniques.
{"title":"A Review of the Applicability of Classical and Extension of Fuzzy Logic Approaches to Project Decision-Making using Real Options","authors":"I. Kouatli, Skander Ben Abdallah, Abbas Terhini, Hiba Naccash","doi":"10.2174/2666294901666220428145618","DOIUrl":"https://doi.org/10.2174/2666294901666220428145618","url":null,"abstract":"\u0000\u0000Real options theory allows taking into account the value of some sources of managerial flexibility and therefore assessing more accurately a project value. The positive value of flexibility results from limiting the impacts of adverse events while taking advantage of positive ones. One of the main lessons is that uncertainty adds value in the presence of flexibility. Ambiguous parameters that have a significant effect on the project value are usually represented as fuzzy sets using Zadeh’s classical theory of Fuzzy logic” (also termed as “type-1”). However, there have been so many derivatives and expansions of the fuzzy set theories developed by different researchers. This paper reviews the applicability of ROA to fuzzy sets (classical and extended) implementation to decision-making for large projects where project timing and uncertainty are key parameters affecting the project value. The objective of this review is to identify the research gap as well as provide an elementary guide of the applicability of such techniques.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134525697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-24DOI: 10.2174/2666294901666220324121629
Gizem Temelcan, H. Kocken, Inci Albayrak
Transport models have wide application areas in the real world and they play an important role in reducing transportation costs, increasing service quality, etc. These models can contain uncertain transportation costs, supply or demand capacities of the product. Hence, it would be effective to model the vagueness arising from customer demands, economic conditions, technical or non-technical uncertainties because of the uncontrollable factors, we focus on developing a mathematical solution approach to the fuzzy transportation problems. In this paper, an integrated approach is proposed for the solution of the fuzzy linear transportation problem that has fuzzy cost coefficients in the objective function. Since TP is encountered frequently in real life in the national and international environment, it is considered that proposing a new solution method to this problem will be useful. Fuzzy cost coefficients are taken as trapezoidal fuzzy numbers due to their widespread use in the literature. Firstly, the fuzziness is removed by converting the original single-objective fuzzy transportation problem into a crisp Multi-Objective Linear Programming Problem (MOLPP). After the classical payoff matrix is constructed, ratio matrices are obtained to scale the objectives. Then, an approach based on game theory is implemented to solve the MOLPP which is handled as a zero-sum game. Creating different ratio matrices in the game-theory part of the approach can generate compromise solutions to present to the decision makes. To demonstrate the effectiveness of the proposed approach, two numerical examples from the literature are solved. While the same solution was obtained in one of the examples, a different compromise solution set is generated which could be presented to the decision-maker in the other example. In this paper, we developed a novel game-theory based approach to the fuzzy transportation problem. The proposed approach enables to overcome of the non-linear structure due to the uncertainty in the cost coefficients. The biggest advantage of the proposed approach can generate more than one optimal solution to offer the decision-maker.
{"title":"A Game Theory based Approach to Fuzzy Linear Transportation Problem","authors":"Gizem Temelcan, H. Kocken, Inci Albayrak","doi":"10.2174/2666294901666220324121629","DOIUrl":"https://doi.org/10.2174/2666294901666220324121629","url":null,"abstract":"\u0000\u0000Transport models have wide application areas in the real world and they play an important role in reducing transportation costs, increasing service quality, etc. These models can contain uncertain transportation costs, supply or demand capacities of the product. Hence, it would be effective to model the vagueness arising from customer demands, economic conditions, technical or non-technical uncertainties because of the uncontrollable factors, we focus on developing a mathematical solution approach to the fuzzy transportation problems.\u0000\u0000\u0000\u0000In this paper, an integrated approach is proposed for the solution of the fuzzy linear transportation problem that has fuzzy cost coefficients in the objective function. Since TP is encountered frequently in real life in the national and international environment, it is considered that proposing a new solution method to this problem will be useful.\u0000\u0000\u0000\u0000Fuzzy cost coefficients are taken as trapezoidal fuzzy numbers due to their widespread use in the literature. Firstly, the fuzziness is removed by converting the original single-objective fuzzy transportation problem into a crisp Multi-Objective Linear Programming Problem (MOLPP). After the classical payoff matrix is constructed, ratio matrices are obtained to scale the objectives. Then, an approach based on game theory is implemented to solve the MOLPP which is handled as a zero-sum game.\u0000\u0000\u0000\u0000Creating different ratio matrices in the game-theory part of the approach can generate compromise solutions to present to the decision makes. To demonstrate the effectiveness of the proposed approach, two numerical examples from the literature are solved. While the same solution was obtained in one of the examples, a different compromise solution set is generated which could be presented to the decision-maker in the other example.\u0000\u0000\u0000\u0000In this paper, we developed a novel game-theory based approach to the fuzzy transportation problem. The proposed approach enables to overcome of the non-linear structure due to the uncertainty in the cost coefficients. The biggest advantage of the proposed approach can generate more than one optimal solution to offer the decision-maker.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127379272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-07DOI: 10.2174/2666294901666220307161621
Ibrahim Yazici, Orhan Engin
Process mining is used extensively in recent years to develop the steps of the business. Also, process mining is an important technique to remove waste and reduce process costs. The aims of this study indicate that congestion, workflow which lived a long time, and stuff or system statistics in the banking real estate transaction process. In this work, the process mining practice is applied in bank business loans. In the bank process, the most used and more complicated business is a bank loan transaction. The process mining implementation pattern is created with sample and flow gains of process development. Then, the new workflow designed and the pattern is executed. In this study, in the first stage of the total loan period, 7.84 hours of earnings are obtained. Visualizations of the process have been affected with the help of fuzzy model algorithms necessary to the huge number of incidents and activities. Workflow analysis and gather information for studies were set up to be effortless with the support of fuzzy models. As a result of the analysis based on the flows, the knowledge pool is created by getting the knowhows such as the average duration of the process and the deviations in the users or systems. The results indicated that process mining is a significant methodology for developing bank loan transactions and enhancement their performance.
{"title":"Application of Process Mining with Fuzzy Models to Loan Processing","authors":"Ibrahim Yazici, Orhan Engin","doi":"10.2174/2666294901666220307161621","DOIUrl":"https://doi.org/10.2174/2666294901666220307161621","url":null,"abstract":"\u0000\u0000Process mining is used extensively in recent years to develop the steps of the business. Also, process mining is an important technique to remove waste and reduce process costs. The aims of this study indicate that congestion, workflow which lived a long time, and stuff or system statistics in the banking real estate transaction process.\u0000\u0000\u0000\u0000In this work, the process mining practice is applied in bank business loans. In the bank process, the most used and more complicated business is a bank loan transaction. The process mining implementation pattern is created with sample and flow gains of process development. Then, the new workflow designed and the pattern is executed.\u0000\u0000\u0000\u0000In this study, in the first stage of the total loan period, 7.84 hours of earnings are obtained. Visualizations of the process have been affected with the help of fuzzy model algorithms necessary to the huge number of incidents and activities. Workflow analysis and gather information for studies were set up to be effortless with the support of fuzzy models. As a result of the analysis based on the flows, the knowledge pool is created by getting the knowhows such as the average duration of the process and the deviations in the users or systems.\u0000\u0000\u0000\u0000The results indicated that process mining is a significant methodology for developing bank loan transactions and enhancement their performance.\u0000","PeriodicalId":436903,"journal":{"name":"Journal of Fuzzy Logic and Modeling in Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132181356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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