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.

Autorentext
Lionel Amodeo obtained his Engineering Degree in Mechanical Engineering from the National Engineer School of Belfort (France) in 1993, and the same year, his master's degree in Automatic and Production Management from the University of Franche Comté (France). In 1999, he received his Ph.D. degree in Automatic and Computer Sciences from the University of Franche Comté (France). Then he became an Associated Professor at the University of Technology of Troyes (UTT) in 2000. Since 2010, he is a full Professor at UTT, where he is the head of the Engineer Degree in Industrial Systems with more than 400 students. His research interests include logistic and production systems optimization, scheduling, system design, facility layout and inventory problems.
He has published more than 260 contributions including 4 books, 11 book chapters, 38 papers in international journals and over 190 communications in conference proceedings. He is member of Editorial Board of journals: International Journal of Engineering Mathematics, Hindawi Publishing Corporation, Journal of Modelling and Simulation of Systems, Journal of Studies on Manufacturing.
He is also member of several international conference committees (about 25 conferences) (MIC'2017, MIM 2016, INCOM2015, IESM 2015), member of more than 15 organization committees of conferences. He organized and or Chair more than 30 tracks or sessions in conferences. He is reviewer for more than 18 international journals. He supervises or supervised 16 Ph.D thesis and 32 Master of Sc. Student. He is expert for French Research Agency (ANR), and for different agencies such as French AERES Agency, Natural Sciences and Technology Research Fund (FRQNT, Canada), and Austrian Research Fund (FWF). He is member of the Technical Committee IFAC T.7.4 Transportation Systems.
El-ghazali Talbi received the Master and Ph.D degrees in Computer Science, both from the Institut NationalPolytechnique de Grenoble in France. Then he became an Associate Professor in Computer Sciences at the University of Lille (France). Since 2001, he is a full Professor at the University of Lille and the head of the optimization team of the Computer Science laboratory (CRISTAL). His current research interests are in the field of multi-objective optimization, parallel algorithms, metaheuristics, combinatorial optimization, cluster and grid computing, hybrid and cooperative optimization, and application to logistics/transportation and bio-medical.
Professor Talbi has to his credit more than 150 publications in journals, chapters in books, and conferences. He is the co-editor of 6 books. He was a guest editor of more than 15 special issues in different journals (Journal of Heuristics, Journal of Parallel and Distributed Computing, European Journal of Operational Research, Theoretical Computer Science, Journal of Global Optimization). He is the head of the INRIA Dolphin project and was the director of the bioinformatics platform of the Genopole of Lille. He has many collaborative national, European and international projects.
He is the co-founder and the coordinator of the research group dedicated to Metaheuristics: Theory and Applications (META). He is the founding co-chair of the NIDISC workshop on nature inspired computing (IEEE/ACM IPDPS) and META (Int. Conf. on Metaheuristics). He served in different capacities on the programs of more than 100 national and international conferences. He is also the organizer of many conferences (e.g. EA'2005, ROADEF'2006, META'2008, IEEE AICCSA'2010, META'2014, MIC'2015, META'2016, BIOMA'2018).
Farouk Yalaoui obtained his Engineering degree in Industrial Engineering from the Polytechnics School of Algiers (Algeria) in 1995, his master's degree in Industrial System Engineering from Polytechnics Institute of Lorraine (Nancy, France) in 1997, his Ph.D. degree in Production Management from the Troyes University of Technology (UTT) in 2000 and followed by a Habilitation à diriger les recherches (Dr. Hab) from Compiegne University of Technology (UTC) in 2006. He is currently a full Professor at Troyes University of Technology, France, where he is the head of Optimisation Industrial systems Optimisation Lab (Research Team), Charles Dealaunay Institute (ICD), UMR CNRS 6281. His research topic focuses on the scheduling problems, system design, operations research, modeling, analysis and optimization of logistic and production systems, reliability and maintenance optimization and on optimization problems in general.
He is author or co-author of a pattern and more than 330 contributions, p...

Inhalt
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 5. A re-characterization of hyper-heuristics.- by Jerry Swan, Patrick De Causmaecker, Simon Martin, Ender Ozcan.- Chapter 6. POSL: A Parallel-Oriented metaheuristic-based Solver Language.- by Alejandro Reyes Amaro, Eric Monfroy and Florian Richoux.- Chapter 7. An Extended Neighborhood Vision for Hill-climbing Move Strategy Design.- by Sara Tari, Matthieu Basseur and Adrien Goeffon.- Chapter 8. Theory driven design of efficient genetic algorithms for a classical graph problem.- by Dogan Corus and Per Kristian Lehre.- Chapter 9. On the impact of representation and algorithm selection for optimisation in process design: motivating a meta-heuristic framework.- by Eric S. Fraga, Abdellah Salhi and El-Ghazali Talbi.- Chapter 10. Manufacturing Cell Formation Problem using Hybrid Cuckoo Search Algorithm.- by Bouchra Karoum, Bouazza Elbenani, Noussaima El Khattabi and Abdelhakim A. El Imrani.- Chapter 11. Hybridization of Branch and Bound Algorithm with Metaheuristics for Designing Reliable Wireless Multimedia Sensor Network.- by Omer Ozkan, Murat Ermis, and Ilker Bekmezci.- Chapter 12. A hybrid MCDM approach for supplier selection with a case study.- by Hanane Asselaou, Brahim Ouhbi and Bouchra Frikh.- Chapter 13. A Multi-Objective Optimization via Simulation framework for restructuring traffic networks subject to increases in population.- by Enrique…