Babak Zolghadr-Asli – författare

Planning and Management for Sustainable Water Resources and Infrastructure under Climate Change explores the critical intersection of climate change, and sustainable water resources and infrastructure. With a diverse range of chapters covering topics from public participation and water governance to smart technologies, it provides a holistic understanding of the current concerns, core challenges, and innovative solutions surrounding water infrastructure and resilience. The book offers necessary information on current approaches for adaptation and mitigation strategies including but not limited to AI, IoT, and remote sensing. The implications of climate change for agriculture and aquaculture, the complexities of water and climate change governance, and the pressing issues of droughts, seawater intrusion, and intermittent water supply are discussed. It also examines various impacts of climate change on water resources and infrastructure with real-world case studies around the globe. By addressing these multifaceted topics, the book equips readers with the knowledge and strategies to navigate the evolving issues of water management in the face of a changing climate.Offers real-world case studies in every chapterExploration of innovative solutions for sustainable water resources management and climate-resilient infrastructureProvides a comprehensive understanding of climate-change-related aspects to water resources and infrastructure

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming.These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in.Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming.These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in.Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.

Clear and effective instruction on MADM methods for students, researchers, and practitioners.A Handbook on Multi-Attribute Decision-Making Methods describes multi-attribute decision-making (MADM) methods and provides step-by-step guidelines for applying them. The authors describe the most important MADM methods and provide an assessment of their performance in solving problems across disciplines. After offering an overview of decision-making and its fundamental concepts, this book covers 20 leading MADM methods and contains an appendix on weight assignment methods. Chapters are arranged with optimal learning in mind, so you can easily engage with the content found in each chapter. Dedicated readers may go through the entire book to gain a deep understanding of MADM methods and their theoretical foundation, and others may choose to review only specific chapters. Each standalone chapter contains a brief description of prerequisite materials, methods, and mathematical concepts needed to cover its content, so you will not face any difficulty understanding single chapters. Each chapter: Describes, step-by-step, a specific MADM method, or in some cases a family of methodsContains a thorough literature review for each MADM method, supported with numerous examples of the method's implementation in various fieldsProvides a detailed yet concise description of each method's theoretical foundationMaps each method's philosophical basis to its corresponding mathematical frameworkDemonstrates how to implement each MADM method to real-world problems in a variety of disciplinesIn MADM methods, stakeholders' objectives are expressible through a set of often conflicting criteria, making this family of decision-making approaches relevant to a wide range of situations. A Handbook on Multi-Attribute Decision-Making Methods compiles and explains the most important methodologies in a clear and systematic manner, perfect for students and professionals whose work involves operations research and decision making.

This book provides a comprehensive yet fresh perspective for the cutting-edge CI-oriented approaches in water resources planning and management.