Optimization in Industrial Engineering: From Classical Methods to Modern Metaheuristics with MATLAB Applications - Rilegato

Cuevas, Erik; Rosas Caro, Julio Cesar; Rodriguez, Alma; Gonzįlez Ayala, Paulina; Alejo Reyes, Avelina

Rilegato

ISBN 10: 3031740262 ISBN 13: 9783031740268

Casa editrice: Springer-Verlag GmbH, 2025

Riassunto

This textbook provides readers with a comprehensive exploration of optimization techniques in industrial engineering, with a specific focus on the Economic Order Quantity (EOQ) problem. It strikes a unique balance by thoroughly discussing the underlying concepts and theories, equipping the reader with the knowledge needed to develop their own programs for solving complex optimization problems in the field. A distinctive feature of this book is its extensive use of MATLAB implementations, which serves as a practical tool to bridge the gap between theory and real-world application. The book is structured with the understanding that learning is accelerated when theoretical concepts are complemented by practical, code-based problem-solving examples. This approach is particularly beneficial for students who may have a weaker background in mathematics, as it demonstrates the practicality and effectiveness of optimization in a more accessible manner. The inclusion of ready-made code examples not only makes the subject matter more engaging for students but also encourages them to experiment, modify, and enhance the code with their own ideas. This method of learning is designed to be less daunting and more stimulating, particularly for those who might feel overwhelmed by the prospect of developing complex programs from scratch. The book's approach is aimed at demystifying the complexities of optimization in industrial engineering, making it more approachable and interesting for students and practitioners alike.

Diverging from other texts that primarily focus on classical techniques for addressing optimization problems in industrial engineering, this book sets itself apart by delving into modern metaheuristic methods. Metaheuristic techniques have gained recognition for their efficacy in tackling complex problems that are often laden with diverse and challenging constraints. These methods, which include algorithms such as simulated annealing, and particleswarm optimization, offer a more dynamic and flexible approach to finding solutions compared to traditional methods. They are particularly adept at navigating vast search spaces and identifying optimal or near-optimal solutions in scenarios where conventional approaches might struggle. This inclusion of metaheuristic methods gives the book a unique quality, providing readers with a comprehensive understanding of both the established foundations and the cutting-edge advancements in the field of optimization. The book's exploration of these advanced techniques not only broadens the reader's knowledge base but also equips them with the tools to effectively solve more intricate and nuanced problems encountered in industrial engineering. This dual focus on classical and modern methods positions the book as a valuable and forward-thinking resource in the realm of industrial optimization.

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Informazioni sull?autore

Dr. Erik Cuevas received his B.S. degree with distinction in Electronics and Communications Engineering from the University of Guadalajara, Mexico, in 1995, the M.Sc. degree in Industrial Electronics from ITESO, Mexico, in 2000, and the Ph.D. degree from Freie Universität Berlin, Germany in 2006. Since 2006 he has been with the University of Guadalajara, where he is currently a full-time Professor in the Department of Computer Science. Since 2008, he is a member of the Mexican National Research System (SNI III). He is the author of several books and articles. A list of his books and publications can be seen in the CV attached to this application. His current research interest includes Meta-heuristics, computer vision, and mathematical methods. He serves as an editor in Expert System with Applications, ISA Transactions, and Applied Soft Computing, Applied Mathematical Modeling and Mathematics and Computers in Simulation.

Julio C. Rosas-Caro received a B.S. in electronics and an M.S. in E.E. from the Tec de Cd. Madero, Mexico, in 2004 and 2005, respectively, and the Ph.D. in E.E. from the Cinvestav del IPN, Mexico, in 2009. He has been a Visiting Scholar at several institutions, such as the Michigan State University, the University of Colorado Denver, Ontario Tech University, and The University of Sheffield. Dr. Rosas-Caro is the author of several scientific articles in the field of engineering, an Associate Editor of the IEEE Latin America Transactions, an Academic Editor of the International Transactions on Electrical Energy Systems, and he has been invited to be a lead guest editor in several special issues of scientific Journals. He is currently a Professor at Universidad Panamericana, Mexico. His research interest is in power electronics, including DC-to-DC converters, flexible alternating current transmission system devices, power converter topologies, applications, and optimization.

Avelina Alejo-Reyes received a B.S. degreein industrial engineering and an M. degree from the Tecnologico de Cd. Madero, Mexico, in 2005 and 2007, respectively. Madero, and the Ph.D. degree in engineering from Universidad Panamericana, Guadalajara, Mexico, in 2021. She is currently a Professor at Universidad Panamericana, Campus Guadalajara, Mexico. Dr. Alejo-Reyes is the author of several scientific articles in the field of engineering. She is co-author of the book “Recent Metaheuristic Computation Schemes in Engineering” by Springer International Publishing. Her research interest is in Metaheuristic Algorithms, Supplier Selection, Inventory Theory, and optimization.

Paulina Gonzalez-Ayala received a B.S in Civil Engineering and Administration and has a Master in Construction Administration from Universidad Panamericana, Campus Guadalajara. She is currently studying for a PhD in Engineering at the Universidad Panamericana, Campus Guadalajara. She worked at AVG Latam, a company dedicated to consulting in LeanManufacturing, Six Sigma and Value Engineering, as a junior consultant. She is currently working at the Universidad Panamericana as Secretary of Student Affairs of the Faculty of Engineering and she is also a profesor at the Computer Academy. Her research interest is in Metaheuristic Algorithms, Supplier Selection and optimization.

Alma Rodriguez earned her Bachelor of Science in Industrial Engineering and her Master's degree from CETI, Mexico, in 2005 and 2007, respectively. She went on to achieve her Doctorate in Engineering from the Universidad de Guadalajara, located in Guadalajara, Mexico, in 2021. Dr. Rodriguez has made her mark as an author of numerous engineering-related scientific publications. She contributed as a co-author to the publication "Recent Metaheuristic Computation Schemes in Engineering," released by Springer International Publishing. Her research primarily focuses on the areas of Metaheuristic Algorithms, Supplier Selection, Inventory Theory, and the broader field of optimization.

Dalla quarta di copertina

This textbook provides readers with a comprehensive exploration of optimization techniques in industrial engineering, with a specific focus on the Economic Order Quantity (EOQ) problem. It strikes a unique balance by thoroughly discussing the underlying concepts and theories, equipping the reader with the knowledge needed to develop their own programs for solving complex optimization problems in the field. A distinctive feature of this book is its extensive use of MATLAB implementations, which serves as a practical tool to bridge the gap between theory and real-world application. The book is structured with the understanding that learning is accelerated when theoretical concepts are complemented by practical, code-based problem-solving examples. This approach is particularly beneficial for students who may have a weaker background in mathematics, as it demonstrates the practicality and effectiveness of optimization in a more accessible manner. The inclusion of ready-made code examples not only makes the subject matter more engaging for students but also encourages them to experiment, modify, and enhance the code with their own ideas. This method of learning is designed to be less daunting and more stimulating, particularly for those who might feel overwhelmed by the prospect of developing complex programs from scratch. The book's approach is aimed at demystifying the complexities of optimization in industrial engineering, making it more approachable and interesting for students and practitioners alike.

Diverging from other texts that primarily focus on classical techniques for addressing optimization problems in industrial engineering, this book sets itself apart by delving into modern metaheuristic methods. Metaheuristic techniques have gained recognition for their efficacy in tackling complex problems that are often laden with diverse and challenging constraints. These methods, which include algorithms such as simulated annealing, and particleswarm optimization, offer a more dynamic and flexible approach to finding solutions compared to traditional methods. They are particularly adept at navigating vast search spaces and identifying optimal or near-optimal solutions in scenarios where conventional approaches might struggle. This inclusion of metaheuristic methods gives the book a unique quality, providing readers with a comprehensive understanding of both the established foundations and the cutting-edge advancements in the field of optimization. The book's exploration of these advanced techniques not only broadens the reader's knowledge base but also equips them with the tools to effectively solve more intricate and nuanced problems encountered in industrial engineering. This dual focus on classical and modern methods positions the book as a valuable and forward-thinking resource in the realm of industrial optimization.

Dettagli dell?edizione

• Editore: Springer-Verlag GmbH
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 3031740262
• ISBN 13: 9783031740268
• Rilegatura: Copertina rigida
• Numero di pagine: 228
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com