This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy.

The application of contemporary and emerging operational research optimization methods in renewable energy is vital to creating and maintaining sustainable environments across the planet. More research is needed to understand how modern and innovative technological solutions can enhance accessible global energy. Operational Research for Renewable Energy and Sustainable Environments is a critical scholarly resource that examines the efficient use of modern electrical technology and renewable energy sources that have a positive impact on sustainable development. Highlighting topics such as cogeneration thermal modules, photovoltaic (PV) solar, and renewable energy systems (RES) application practices, this publication is geared towards academics, advocates, government officials, policymakers, humanized managers, practitioners, professionals, and students interested in the latest research on renewable energy and clean technology for sustainable rural development.

Modern optimization approaches have attracted many research scientists, decision makers and practicing researchers in recent years as powerful intelligent computational techniques for solving several complex real-world problems. The Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics. Focusing on a variety of methods and systems as well as practical examples, this book is a significant resource for graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modeling uncertain real-world problems.

This book presents the latest developments in optimization and optimal control models; exact, approximate and hybrid methods; and their applications in lean and green supply chains. It examines supply chain network design and modeling, closed loop supply chains, and lean, green, resilient and agile or responsive networks, and also discusses corporate social responsibility and occupational health and safety. It particularly focuses on supply chain management under uncertainty - employing stochastic or nonlinear modeling, simulation based studies and optimization - multi-criteria decision-making and applications of fuzzy set theory, and covers various aspects of supply chain management such as risk management, supplier selection or the design of automated warehouses. Lastly, using experimental applications and practical case studies, it shows the impact of lean and green applications on vehicle/fleet management and operations management.

Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type - 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.

Operation Research methods are often used in every field of modern life like industry, economy and medicine. The authors have compiled of the latest advancements in these methods in this volume comprising some of what is considered the best collection of these new approaches. These can be counted as a direct shortcut to what you may search for. This book provides useful applications of the new developments in OR written by leading scientists from some international universities. Another volume about exciting applications of Operations Research is planned in the near future. We hope you enjoy and benefit from this series!

This book presents the outcomes of the second edition of the International Conference on Intelligent Computing and Optimization (ICO) - ICO 2019, which took place on October 3-4, 2019, in Koh Samui, Thailand. Bringing together research scholars, experts, and investigators from around the globe, the conference provided a platform to share novel research findings, recent advances and innovative applications in the field. Discussing the need for smart disciplinary processes embedded into interdisciplinary collaborations in the context of meeting the growing global populations' requirements, such as food and health care, the book highlights the role of intelligent computation and optimization as key technologies in decision-making processes and in providing cutting edge solutions to real-world problems.

This book includes innovative research work presented at ICO'2018, the 1st International Conference on Intelligent Computing and Optimization, held in Pattaya, Thailand on October 4-5, 2018. The conference presented topics ranging from power quality, reliability, security assurance, cloud computing, smart cities, renewable energy, agro-engineering, smart vehicles, deep learning, block chain, power systems, AI, machine learning, manufacturing systems, and big-data analytics. This volume focuses on subjects related to innovative computing, uncertainty management and optimization approaches to real-world problems in big-data, smart cities, sustainability, meta-heuristics, cyber-security, IoTs, economics and finance, renewable energy, energy and electricity systems, and block chain. Presenting cutting-edge methodologies with real-world application problems and their solutions, the book is useful for researchers, managers, executives, students, academicians, practicing scientists, and decision makers from all around the globe. It offers the academic and the applied communities a compendium and a research resource with significant insights and inspiration for innovative scientific education, investigation and collaboration, to overcome "hard problems" among the emerging challenges today and in the future.

This volume contains contributions from the 11th International Conference on Management Science (CMS 2014), held at Lisbon, Portugal, on May 29-31, 2014. Its contents reflect the wide scope of Management Science, covering different theoretical aspects for a quite diverse set of applications. Computational Management Science provides a unique perspective in relevant decision-making processes by focusing on all its computational aspects. These include computational economics, finance and statistics; energy; scheduling; supply chains; design, analysis and applications of optimization algorithms; deterministic, dynamic, stochastic, robust and combinatorial optimization models; solution algorithms, learning and forecasting such as neural networks and genetic algorithms; models and tools of knowledge acquisition, such as data mining; and all other topics in management science with the emphasis on computational paradigms.

Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy. Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.

This two-volume set constitutes selected papers presented during the First First International Conference on Science, Engineering Management and Information Technology, SEMIT 2022, held virtually in Ankara, Turkey, in February 2–3, 2022 and in September 8-9, 2022.  The  37 papers presented were carefully reviewed and selected from the 261 qualified submissions. The papers are organized in the following topical sections: application of computer science and technology in operations and supply chain management; advances of engineering technology and Artificial Intelligence in application management; human factors management systems based on information technology; technology-aided decision-making: systems, applications, and modern solutions.

This two-volume set constitutes selected papers presented during the First First International Conference on Science, Engineering Management and Information Technology, SEMIT 2022, held virtually in Ankara, Turkey, in February 2–3, 2022 and in September 8-9, 2022.  The 37 papers presented were carefully reviewed and selected from the 261 qualified submissions. The papers are organized in the following topical sections: application of computer science and technology in operations and supply chain management; advances of engineering technology and Artificial Intelligence in application management; technology-aided decision-making: systems, applications, and modern solutions.

Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type – 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.