This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering. The book demonstrates diverse applications of mathematical modeling in various aspects of production, logistic, design, energy, materials, and other engineering areas. The book includes topics in optimization algorithms nature-inspired computing multi-objective optimization hybrid optimization techniques evolutionary algorithms swarm intelligence machine learning for optimization applications of optimization in engineering sustainable engineering solutions big data analytics for optimization metaheuristic approaches cloud computing in optimization cyber-physical systems decision support systems emerging trends in optimization.
Diego Rossit is a full-time adjunct professor at the Universidad Nacional del Sur, Argentina (UNS), and an assistant researcher at CONICET, Argentina. He obtained his Industrial Engineering degree in 2014 and his Ph.D. in Engineering in 2018. His areas of expertise include optimization models and tools, as well as data analysis in industrial engineering applications. These applications encompass the management of transportation systems, urban solid waste management, energy management in households, transportation logistics, production planning, among others. To date, more than 40 indexed papers with an h-index of 11 in Scopus and 27 indexed papers with an h-index of 8 in Web of Science. He has performed research stays at the Universidad de la República (Uruguay), the Australian National University (Australia), the University of Bologna (Italy), the University of Malaga (Spain), the University of Texas at Austin (USA), the Universidad Autónoma del Estado de Morelos (México), and the Universidad Nacional de Asunción (Paraguay).
Carlos Enrique Torres-Aguilar is an associate professor in Mechanical Electrical Engineering Academy of the Engineering and Architecture Academic Division, Universidad Juárez Autónoma de Tabasco, Mexico. In 2023, he obtained a Ph.D. in Mechanical Engineering at the Centro Nacional de Investigación y Desarrollo Tecnológico-TecNM. His research focuses on studying heat transfer mechanisms and fluid mechanics through modeling and simulation of phenomena implementing numerical methods oriented to energy efficiency in buildings and related solar systems. Among his recent studies is the dynamic modeling of constructive and passive ventilation and thermal comfort systems. He has also worked on optimizing numerical solutions of radiative exchange models with participating mediums. During his career, he has published several scientific articles in journals indexed in the Journal Citations Report (JCR) and has participated in national and international conferences.
Adrián Toncovich is an associate professor at Universidad Nacional del Sur. He obtained his degrees in Industrial Engineering and his master degree in Engineering from the Universidad Nacional del Sur (UNS), Argentina, in 2001, and 2006, respectively, his Advanced Studies Diploma from the University of Zaragoza, Spain, in 2009, and his Diploma of Specialization in Production Logistics from the Zaragoza Logistics Center, Spain, in 2009. He is currently a professor of undergraduate courses in Production Planning and Control in the Department of Engineering at UNS and in the Department of Industrial Organization at the National Technological University. He also teaches graduate-level courses at the aforementioned universities on topics related to operations management and supply chain management. His research interests include: production planning and scheduling, supply chain management, industry 4.0 technologies, and multicriteria decision-making and optimization.
