Academic scholars, entrenched in the complexities of various domains, face the daunting task of navigating intricate decision-making scenarios. The prevailing need for efficient and effective decision-making tools becomes increasingly apparent as traditional methodologies struggle to keep pace with the demands of modern research and industry. This pivotal issue necessitates a shift, urging scholars to explore unconventional approaches that can transcend disciplinary boundaries and unlock new dimensions of problem-solving. In response to these pressing challenges, Intelligent Decision Making Through Bio-Inspired Optimization emerges as a beacon of ingenuity. This groundbreaking book transcends usual disciplinary boundaries, seamlessly integrating computer science, artificial intelligence, optimization, and decision science. Its multidisciplinary approach addresses the inherent complexities faced by scholars, offering a comprehensive exploration of nature-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies. The book's core mission is to empower academic scholars with the tools to overcome contemporary decision-making hurdles, providing a holistic understanding of these bio-inspired approaches and their potential to revolutionize the scholarly landscape.

In today's complex and fast-paced world, decision-making is critical to problem-solving across industries and academia. However, traditional optimization techniques often need help to cope with the challenges posed by dynamic and intricate environments. This limitation hampers decision-makers' ability to tackle complex problems and seize opportunities effectively. As such, there is a pressing need for innovative approaches that can enhance decision-making processes, enabling individuals and organizations to navigate uncertainty and achieve optimal outcomes. Bio-Inspired Intelligence for Smart Decision-Making offers a compelling solution to this challenge. By exploring the intersection of bio-inspired optimization techniques and decision-making, this book presents a fresh perspective that can revolutionize decisions. The book introduces readers to powerful bio-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies through a multidisciplinary lens that encompasses computer science, artificial intelligence, optimization, and decision science. These algorithms mimic natural systems' efficiency and adaptability, offering a robust framework for researchers, graduate students, and professionals who are addressing complex decision-making problems in diverse fields.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems. This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.

This book includes selected papers from the 4th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20, 2020. This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Smart cities with various technological innovations have played an important role and influenced society as well. Due to voluminous data transactions within smart cities, security and privacy concerns need to be dealt with. Though taking care of safety and privacy is challenging, it is essential for a smart city to understand the bio-inspired computing paradigms. This book discusses the utilization of bio-inspired computing procedures for effective computational devices. • Discusses real-world usage of bio-inspired computations • Highlights how bio-inspired computations hold the potential to significantly increase network security and privacy • Talks about how society can avoid consequences of cyber security breaches • Examines the combination of bio-inspired computational methods with IoT, AI and big data This book is primarily aimed at graduates, researchers, IT and industry professionals.