Recent Developments in Metaheuristics [Hardcover]

This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.

Chapter 1. Hidden Markov Model Classifier for the Adaptive Particle Swarm Optimization.- by Oussama Aoun, Malek Sarhani and Abdellatif El Afia.- Chapter 2. Possibilistic Framework for Multi-objective Optimization under Uncertainty.- by Oumayma Bahri and Nahla Ben Amor and El-Ghazali Talbi.- Chapter 3. Combining Neighborhoods into Local Search Strategies.- by Renaud De Landtsheer, Yoann Guyot, Gustavo Ospina, and Christophe Ponsard.- Chapter 4 All-Terrain Tabu Search Approaches for Production Management Problems.- by Nicolas Zufferey Jean Respen Simon Thevenin.- Chapter lG