Nonlinear multiobjective optimization is a field that deals with optimization problems involving multiple conflicting objectives. These problems are often complex and require specialized methods to find optimal solutions. The book provides a comprehensive overview of the theory, methods, and applications of nonlinear multiobjective optimization. It covers the theoretical background, including optimality conditions, sensitivity analysis, and duality. The methods section discusses various approaches, including no-preference, a posteriori, a priori, and interactive methods. The book also addresses related issues such as comparing methods, software tools, graphical illustration, and future directions. The author emphasizes the importance of nonlinear multiobjective optimization in real-world applications and highlights the need for new concepts and methods to handle the complexity of such problems. The book is intended for researchers, students, and professionals in fields such as mathematics, engineering, economics, operations research, and management science. It serves as both an introduction to the theory and methodology of nonlinear multiobjective optimization and an extensive reference to related results and methods. The book is written in a clear and structured manner, with a uniform notation and consistent presentation of algorithms and implementation details. It includes a comprehensive bibliography and references to further reading. The author thanks various individuals and institutions for their support and contributions to the publication of the book.Nonlinear multiobjective optimization is a field that deals with optimization problems involving multiple conflicting objectives. These problems are often complex and require specialized methods to find optimal solutions. The book provides a comprehensive overview of the theory, methods, and applications of nonlinear multiobjective optimization. It covers the theoretical background, including optimality conditions, sensitivity analysis, and duality. The methods section discusses various approaches, including no-preference, a posteriori, a priori, and interactive methods. The book also addresses related issues such as comparing methods, software tools, graphical illustration, and future directions. The author emphasizes the importance of nonlinear multiobjective optimization in real-world applications and highlights the need for new concepts and methods to handle the complexity of such problems. The book is intended for researchers, students, and professionals in fields such as mathematics, engineering, economics, operations research, and management science. It serves as both an introduction to the theory and methodology of nonlinear multiobjective optimization and an extensive reference to related results and methods. The book is written in a clear and structured manner, with a uniform notation and consistent presentation of algorithms and implementation details. It includes a comprehensive bibliography and references to further reading. The author thanks various individuals and institutions for their support and contributions to the publication of the book.