Description
Book SynopsisThe authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies.
This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.
Trade Review“I would recommend this book for students in the area of operations research, but also for students and professionals from other fields (like natural sciences or social sciences) who would like not only to apply metaheuristics to solve the problems … but also to understand how they work.” (Marcin Anholcer, zbMATH 1427.90001, 2020)
Table of ContentsProblems, Algorithms, Computational Complexity.- Search Space.- Tabu Search.- Simulated Annealing.- Ant Colony Optimization (ACO).- Non-PSO Optimization.- Firefly Algorithm, Cuckoo Algorithm, Lévy Flights.- Evolutionary Algorithms: Foundations.- Evolutionary Algorithms: Advanced.- Phase Transition in Optimization Problems.- Performance and Limitations of Metaheuristics.- Statistical Analysis of Research Spaces.
