After developing fuzzy set theory, many contributors focused their research on the extension of fuzzy sets and their computational methodologies, strengthening modern science and technology. In some real-life phenomena, the conventional methods and traditional fuzzy sets cannot be explained, whereas the extension of fuzzy sets and effective new computing methods can explain it adequately.

This edited book presents a new view of fuzzy set-measurement methods entitled "Fuzzy Optimization, Decision Making and Operations Research: Theory and Applications", which deals with different perspectives and areas of research. All chapters are divided into three parts: fuzzy optimization, fuzzy decision-making, and fuzzy operation research.

The goal of this book is to provide a relevant methodological framework covering the core fields of fuzzy decision-making method, fuzzy optimization method, fuzzy graphics method, fuzzy operations research, fuzzy optimization using graph theory, fuzzy support systems and its real and industrial applications.

For many people, fuzzy words'' industrial engineering and scientific meanings are still an advanced system for improving modern science and technology. Although fuzzy logic can be applied to many different areas, people do not know how different fuzzy approaches can be applied to various products currently on the market. It is written for professionals who wish to share their expertise, improve their findings, and provide relevant information in the fields of fuzzy methods and their application in decision-making, optimization theory, graph theory and operations research.

The fuzzy logic theory is a branch of mathematics dealing with uncertainty in measurement of any quantity or any estimation. The concept of fuzzy logic uses membership functions. The range of values from various functions or operations determines their construction. A defined rules set can create an application process and membership controls. Fuzzy applications include control system engineering, image processing, power engineering, industrial automation, robotics, consumer electronics and AI. Artificial intelligence, machine learning and expert systems have various applications that address complicated issues. The fuzzy logic inference rules have solved many problems in manufacturing and other industries. Auto engines by Honda, lift control by Mitsubishi Electric, palmtop computers by Hitachi, dishwashers by Matsushita and anti-lock brakes by Nissan are examples of corporations using machine-learning techniques with fuzzy principles. Fuzzy approaches and rule sets interpret computer vision, machine learning and evolution. Fuzzy sets can govern decision rules. Several areas use fuzzy systems in different ways. Computer vision, image processing and meta heuristic evolutionary computing are typical face research applications. Fuzzy theories can optimise and fine-tune the classifier model. Fuzzy theory is used in management, stock market analysis, information retrieval, linguistics, and behavioural science with good results. Fuzzy applications are seen in data mining and stock market prediction. The fuzzy machine learning model in the ensemble pattern accurately classifies and predicts all kinds of tasks. Fuzzy theories help maintain high accuracy. For categorisation and prediction, the ensemble pattern uses fuzzy concepts. The constant growth of fuzzy domain leads to several categorisation and prediction methods. Fuzzy type 2 and intuitionistic fuzzy logic exhibit promise accuracy and versatility. Such fuzzy logic variations can readily overcome the drawbacks of the simple fuzzy model.

The book has been developed keeping in view about readers of different categories starting from the students to the professionals and researchers as well. The development of the  book and  its  content  layout will be done so meticulously proving the  enough  insights  of  the   subjects to the readers so that  the  readers  can easily pursue their research concept from the  book. Overall the book serve as the purpose of repository of good amount of information and their technical presentations.

After developing fuzzy set theory, many contributors focused their research on the extension of fuzzy sets and their computational methodologies, strengthening modern science and technology. In some real-life phenomena, the conventional methods and traditional fuzzy sets cannot be explained, whereas the extension of fuzzy sets and effective new computing methods can explain it adequately.

This edited book presents a new view of fuzzy set-measurement methods entitled "Fuzzy Optimization, Decision Making and Operations Research: Theory and Applications", which deals with different perspectives and areas of research. All chapters are divided into three parts: fuzzy optimization, fuzzy decision-making, and fuzzy operation research.

The goal of this book is to provide a relevant methodological framework covering the core fields of fuzzy decision-making method, fuzzy optimization method, fuzzy graphics method, fuzzy operations research, fuzzy optimization using graph theory, fuzzy support systems and its real and industrial applications.

For many people, fuzzy words'' industrial engineering and scientific meanings are still an advanced system for improving modern science and technology. Although fuzzy logic can be applied to many different areas, people do not know how different fuzzy approaches can be applied to various products currently on the market. It is written for professionals who wish to share their expertise, improve their findings, and provide relevant information in the fields of fuzzy methods and their application in decision-making, optimization theory, graph theory and operations research.

The fuzzy logic theory is a branch of mathematics dealing with uncertainty in measurement of any quantity or any estimation. The concept of fuzzy logic uses membership functions. The range of values from various functions or operations determines their construction. A defined rules set can create an application process and membership controls. Fuzzy applications include control system engineering, image processing, power engineering, industrial automation, robotics, consumer electronics and AI. Artificial intelligence, machine learning and expert systems have various applications that address complicated issues. The fuzzy logic inference rules have solved many problems in manufacturing and other industries. Auto engines by Honda, lift control by Mitsubishi Electric, palmtop computers by Hitachi, dishwashers by Matsushita and anti-lock brakes by Nissan are examples of corporations using machine-learning techniques with fuzzy principles. Fuzzy approaches and rule sets interpret computer vision, machine learning and evolution. Fuzzy sets can govern decision rules. Several areas use fuzzy systems in different ways. Computer vision, image processing and meta heuristic evolutionary computing are typical face research applications. Fuzzy theories can optimise and fine-tune the classifier model. Fuzzy theory is used in management, stock market analysis, information retrieval, linguistics, and behavioural science with good results. Fuzzy applications are seen in data mining and stock market prediction. The fuzzy machine learning model in the ensemble pattern accurately classifies and predicts all kinds of tasks. Fuzzy theories help maintain high accuracy. For categorisation and prediction, the ensemble pattern uses fuzzy concepts. The constant growth of fuzzy domain leads to several categorisation and prediction methods. Fuzzy type 2 and intuitionistic fuzzy logic exhibit promise accuracy and versatility. Such fuzzy logic variations can readily overcome the drawbacks of the simple fuzzy model.

The book has been developed keeping in view about readers of different categories starting from the students to the professionals and researchers as well. The development of the  book and  its  content  layout will be done so meticulously proving the  enough  insights  of  the   subjects to the readers so that  the  readers  can easily pursue their research concept from the  book. Overall the book serve as the purpose of repository of good amount of information and their technical presentations.