Multi-Objective Combinatorial Optimization Problems and Solution Methods

Mehdi Toloo · Siamak Talatahari · Iman Rahimi

2022年2月 · Academic Press

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Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. - Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications - Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature - Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms

作者简介

Dr. Mehdi Toloo is a Full Professor in the Faculty of Economics, Technical University of Ostrava, and Faculty of BusinessAdministration, University of Economics, Prague, Czech Republic. He received his Masters of Science in Applied Mathematics and his Ph.D. in Operations Research. Dr. Toloo’s areas of interest include Operations Research, Decision Analysis, PerformanceEvaluation, Multi-Objective Programming, and Mathematical Modelling. He has contributed to numerous international conferencesas a chair, keynote speaker, and member of the scientific committee. He is an area editor for the Elsevier journal Computers andIndustrial Engineering and an associate editor for RAIRO-Operations Research. His publications include the book Introduction toScientific Computing: 100 Problems and Solutions in Pascal and papers in top-tier journals such as Applied Mathematics andComputers, Applied Mathematic Modeling, Expert Systems with Applications, and Computers and Mathematics with Applications.

Dr. Siamak Talatahari received his Ph.D degree in Structural Engineering from University of Tabriz, Iran. After graduation, hejoined the University of Tabriz where he is presently Professor of Structural Engineering. He is the author of more than 100 paperspublished in international journals, 30 papers presented at international conferences and 8 international book chapters. Dr. Talataharihas been recognized as Distinguished Scientist in the Ministry of Science and Technology and as Distinguished Professor at theUniversity of Tabriz. He also teaches at the Yakin Dogu University, Nicosia, Cyprus. In addition, he is a co-author with our authorXin-She Yang of Swarm Intelligence and Bio-Inspired Computation: Structural Optimization Using Krill Herd Algorithm;Metaheuristics in Water, Geotechnical and Transport Engineering, and Metaheuristic Applications in Structures andInfrastructures, all published by as Insights by Elsevier.

Iman Rahimi, PhD, is a distinguished research scholar at the University of Technology Sydney, Australia, specializing in machine learning, optimization, and applied mathematics. He holds dual doctorates in Industrial Engineering and Computer Science, along with a BSc and MSc in Applied Mathematics. Dr. Rahimi has authored and edited several influential books, including titles on evolutionary computation and big data analytics, and has contributed extensively to academic literature as a reviewer for high-ranking journals. His editorial experience spans multiple publications, and he has received numerous international awards and research grants, highlighting his significant contributions to the field. With a robust background in operations research, Dr. Rahimi continues to advance knowledge in multiobjective optimization and its applications in various industries.