Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Prioritizing Barriers and Strategies Mapping in Business Intelligence Projects Using Fuzzy AHP TOPSIS Framework in Developing Country

Business Intelligence (BI) is an essential technology in an increasingly competitive landscape since it helps make decisions more accurately. To achieve an effective BI implementation, the organization must formulate the right strategy to overcome its challenges. This research aimed to develop a framework to map barriers into strategies using qualitative and quantitative methods. The qualitative approach is driven by interviewing BI experts to validate the barriers and strategies previously obtained. Based on the interview, there are 19 barriers and 9 strategies that could be used. The quantitative approach compiles a priority list of the most significant barriers and the most effective strategies to overcome these barriers using fuzzy AHP TOPSIS, an MCDM method to eliminate inconsistencies during ranking. The results indicate that the lack of collaboration between the IT and BI departments, the BI implementation demands to be done quickly, and low data quality are the main barriers that hinder BI's success. This research also found that business people's involvement in a BI project is the best strategy to overcome the obstacles. The chances of a successful BI implementation will increase by having good cooperation between IT and business units within the company. Doi: 10.28991/ESJ-2022-06-02-010 Full Text: PD

Prioritization of public services for digitalization using fuzzy Z-AHP and fuzzy Z-WASPAS

In this paper, public services are analyzed for implementations of Industry 4.0 tools to satisfy citizen expectations. To be able to prioritize public services for digitalization, fuzzy Z-AHP and fuzzy Z-WASPAS are used in the analysis. The decision criteria are determined as reduced cost, fast response, ease of accessibility, reduced service times, increase in the available information and increased quality. After obtaining criteria weights using fuzzy Z-AHP, health care services, waste disposal department, public transportation, information services, social care services, and citizen complaints resolution centers are compared using fuzzy Z-WASPAS that is proposed for the first time in this paper. Results show that health care services have dominant importance for the digitalization among public services.WOS:000604482500002Science Citation Index ExpandedQ2Article; Early AccessUluslararası işbirliği ile yapılmayan - HAYIROcak2021YÖK - 2020-2

Advanced decision making in sustainable city logistics projects : criteria and, risk identification and assessment

Les villes sont les lieux de la plus grande concentration d'activités sociales et économiques. La logistique est l'une des plus importants éléments de la durabilité et de l'économie d’une la ville. Pour la logistique urbaine, il est nécessaire de prendre en compte les caractéristiques de la ville et les objectifs de toutes les parties prenantes (expéditeurs, destinataires, transporteurs, prestataires de services logistiques, résidents, gouvernement de la ville). Les plans de logistique urbaine durable pourraient avoir un impact significatif sur la qualité de la vie en milieu urbain. L'évaluation d'initiatives de logistique de ville durable (SCLI) telles que les centres de distribution urbains, la tarification de la congestion, le délai de livraison et les restrictions d'accès est un problème complexe, car plusieurs critères et contraintes subjectifs et objectifs doivent être pris en compte. Les administrations municipales investissent dans des initiatives de logistique urbaine durable telles que les centres de distribution urbains, la tarification de la congestion, le calendrier de livraison et les restrictions d'accès afin d'améliorer les conditions de transport de marchandises dans les villes et de réduire leurs impacts négatifs sur les citoyens et leur environnement. Cependant, il y a toujours des risques dynamiques associés à la sélection. L’analyse des risques des initiatives de logistique urbaine est une tâche complexe en raison de la multiplicité des facteurs de risque et de leurs dépendances. Bien qu'il n'y ait pas beaucoup d'études sur les risques liés à la logistique urbaine, aucune attention n'a été portée à l'analyse des risques liés à la logistique urbaine en prenant en compte les dépendances entre les facteurs de risque et leurs critères. Considérer les dépendances entre les facteurs de risque pourrait conduire à une analyse plus précise des risques et augmenter le taux de réussite de la sélection des initiatives de logistique urbaine. Méthodes: pour résoudre ce problème, nous proposons un outil avancé d'aide à la décision appelé «cartescognitives floues» (FCM), capable de gérer les risques associés à des systèmes aussi complexes. La FCM représente avec précision le comportement de systèmes complexes et peut prendre en compte les incertitudes, les informations imprécises, les interactions entre les facteurs de risque, la rareté de l'information et les opinions de plusieurs décideurs. En outre, il pourrait être appliqué à différents problèmes de prise de décision liés aux initiatives de logistique de ville durable (SCLI). Par conséquent, l'outil proposé aiderait les praticiens à gérer les risques liés à la logistique urbaine d'une manière plus efficace et proactive et offrirait de meilleures solutions d'atténuation des risques. Dans les études précédentes, les méthodes de décision multicritères étaient principalement utilisées pour l'évaluation, la comparaison et la sélection d'initiatives logistiques de villes en fonction des effets obtenus ou prévus résultant de leur introduction dans divers environnements urbains. Afin d'évaluer l'adéquation des solutions conceptuelles aux exigences des différentes parties prenantes et conformément aux attributs spécifiques de l'environnement urbain, il convient de définir des solutions conceptuelles associant différentes initiatives de logistique urbaine en utilisant un processus artificiel; outils de renseignement, y compris la FCM.The cities are the places of the largest concentration of social activities and economic. Logistics is one of the most important for the sustainability and the economy of the city. Inselecting the city logistics concept, it is necessary to consider the characteristics of the city and the goals of all the stakeholders (shippers, receivers, carriers, logistics service providers, residents, city government). Sustainable city logistics (SCL) plans could significantly affect the quality of life in the urban environment. Evaluating sustainable city logistics initiatives (SCLI) such as urban distribution centres, congestion pricing, delivery timing and access restrictions is a complex problem since several subjective and objective criteria and constraints should be considered. Municipal administrations are investing in sustainable city logistics initiatives (SCLI) such as urban distribution centres, congestion pricing, delivery timing and access restrictions in order to improve the condition of goods transport in cities and reduce their negative impacts on citizens and their environment. However, there is always some dynamic risks associated that should be selected. Risk analysis of sustainable city logistics initiatives is a complex task due to consisting of many risk factors with dependencies among them. Although there are no lots of studies on sustainable city logistics risks, no attention has been paid to the risk analysis of sustainable city logistics by considering the dependencies among risk factors and their criteria. Considering the dependencies among risk factors could lead to more precise risks analysis and increase the success rate of selecting sustainable city logistics initiatives. Methods: To address this, we are proposing an advanced decision support tool called "Fuzzy Cognitive Maps" (FCM) which can deal with risks of such complicated systems. FCM represents the behaviour of complex systems accurately and is able to consider uncertainties, imprecise information, the interactions between risk factors, information scarcity, and several decision maker's opinions. In addition, it could be applied to different decision makings problems related to sustainable city logistics initiatives (SCLI). Therefore, the proposed tool would help practitioners to manage sustainable city logistics risks in a more effective and proactive way and offer better risk mitigation solutions. In previous studies, multi-criteriadecision-making methods are mainly used for the evaluation, comparison and selection of individual sustainable city logistics initiatives in relation to the achieved or planned effects resulting from their introduction in various urban environments. In order to assess the suitability of the conceptual solutions to the requirements of different stakeholders, and in accordance with the specific attributes of the urban environment, there is the definition of conceptual solutions that combine different sustainable city logistics initiatives by using an artificial; intelligence tools including FCM

Integrating fuzzy theory and visualization for QoS-aware selection of SaaS in cloud e-Marketplaces

Most cloud service e-marketplaces incorporate basic features like search and billing but lack more sophisticated elements that optimise users’ experience. The cognitive demands of searching for and evaluating multiple cloud SaaS along multiple QoS criteria can be overwhelming, giving rise to what Alvin Toffler called choice overload. There is a need to integrate mechanisms that handles the vagueness that characterises the human decision-making process when finding suitable services. The objective of this paper is to reduce cognitive overload during cloud service selection in e-marketplaces by employing low cognitive demanding tools that leverage the dynamics of human expressions. We proposed a QoS-aware SaaS ranking and selection framework that integrates fuzzy theory and information visualisation for optimal decision-making in cloud e-marketplaces. An illustrative case study of Customer-Relationship-Management-as-a-Service e-marketplace demonstrated the framework’s plausibility. The demonstration shows that our framework is a viable approach to rank and select SaaS in cloud e-marketplaces ina way that satisfactorily serves both the users of the platform and can potentially drive the business objectives of the e-marketplace

Rapid manufacturing as an enabling technology in supply chain improvements

Rapid Manufacturing (RM), the direct production of a finished product, is a newly emerging manufacturing technology projected to provide supply chain benefits. However, there is a lack of information detailing its expected benefits in the supply chain. Robust, generic guidelines are needed in order to help practitioners cope with this emerging manufacturing technology. The aim of this research is to establish the benefits and difficulties of RM in supply chain along with an indication of the possible changes required to sustain RM as a future potential manufacturing machine. There is a common consensus that an information system is required for the effective functioning of the supply chain. This study concerns the integration of RM within the supply chain information system. As the parameters of the supply chain and information system applications are many, the research is focused on a specific set of parameters. Critically, the focus of the study is on identifying how RM would improve customisation and reduce lead time and inventory on products. The application of the information system is also examined. With the research focused towards the future, technological forecasting of RM's impact on the supply chain and information system is considered. Adopting scenarios the application of RM is explored in various supply chain structures, A performance analysis of RM is undertaken by means of a questionnaire involving people with relevant experience. From the results, decision analysis on supply chain structures adopting RM is undertaken to select a suitable structure for the manufacture of a product through RM. A decision-analysis tool kit is developed and products are grouped according to the criteria suitable for the application of RM. Validation of the decision-analysis tool kit and the suitability of RM in the supply chain is carried out via a case study of the production of a prosthetic product. The results how that the developed decision-analysis system works simply and effectively. RM is suitable for application in various supply chain structures; it provides a new dimension ('in-depth') in customising products as well as reducing inventory and lead-time. However, the full effectiveness of RM is entirely dependent on the supply chain structure adopted. Hence, some changes required to sustain RM as a future potential manufacturing system are suggested. Finally, the case study is used to illustrate the possible application of RM in improving selected parameters of supply chain performance for the manufacture of customised products

Multiple-Criteria Decision Making

Decision-making on real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with imprecise, ambiguous, or vague data.This Special Issue, “Multiple Criteria Decision Making”, aims to incorporate recent developments in the area of the multi-criteria decision-making field. Topics include, but are not limited to:- MCDM optimization in engineering;- Environmental sustainability in engineering processes;- Multi-criteria production and logistics process planning;- New trends in multi-criteria evaluation of sustainable processes;- Multi-criteria decision making in strategic management based on sustainable criteria

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature