Patrick Siarry is a Professor of Automatics and Informatics at the University of Paris-Est Créteil, where he leads the Image and Signal Processing team in the Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi). He has considerable teaching, research and writing experience in the areas of signal processing, control, artificial intelligence, operations research, and optimization. He presently serves as an Associate Editor of the journal Information Sciences and the journal Engineering Applications of Artificial Intelligence.

“The book’s chapters are written by prominent researchers in the metaheuristics field. They include adequate references, and many contain annotated bibliographies. … This book will be useful for academicians, problem solvers in industry, practitioners, students, and researchers.” (S. V. Nagaraj, Computing Reviews, January, 2018)​

• Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.

Patrick Siarry is a Professor of Automatics and Informatics at the University of Paris-Est Créteil, where he leads the Image and Signal Processing team in the Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi). He has considerable teaching, research and writing experience in the areas of signal processing, control, artificial intelligence, operations research, and optimization. He presently serves as an Associate Editor of the journal Information Sciences and the journal Engineering Applications of Artificial Intelligence.

“The book’s chapters are written by prominent researchers in the metaheuristics field. They include adequate references, and many contain annotated bibliographies. … This book will be useful for academicians, problem solvers in industry, practitioners, students, and researchers.” (S. V. Nagaraj, Computing Reviews, January, 2018)​

• Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.

Patrick Siarry is a Professor of Automatics and Informatics at the University of Paris-Est Créteil, where he leads the Image and Signal Processing team in the Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi). He has considerable teaching, research and writing experience in the areas of signal processing, control, artificial intelligence, operations research, and optimization. He presently serves as an Associate Editor of the journal Information Sciences and the journal Engineering Applications of Artificial Intelligence.

“The book’s chapters are written by prominent researchers in the metaheuristics field. They include adequate references, and many contain annotated bibliographies. … This book will be useful for academicians, problem solvers in industry, practitioners, students, and researchers.” (S. V. Nagaraj, Computing Reviews, January, 2018)​

• Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.