Recent Developments in Metaheuristics [electronic resource] /
Amodeo, Lionel.editor.
Talbi, El-Ghazali.editor.
Yalaoui, Farouk.editor.
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.
Includes bibliographical references and index.
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 Gabriel Baquela and Ana Carolina Olivera -- Chapter 14. Hybrid metaheuristic for air traffic management with uncertainty -- by S. Chaimatanan and D. Delahaye and M. Mongeau -- Chapter 15. Sampling-Based Genetic Algorithms for the Bi-Objective Stochastic Covering Tour Problem -- by Michaela Zehetner and Walter J. Gutjahr -- Chapter 16. A metaheuristic framework for dynamic network flow problems -- by M. Hajjem, H. Bouziri and E.G. Talbi -- Chapter 17. A Greedy Randomized Adaptive Search for the Surveillance Patrol Vehicle Routing Problem -- by Simona Mancini -- Chapter 18. Strip Algorithms as an Efficient Way to Initialise Population-based Metaheuristics -- by Birsen ˙Irem Selamoglu, Abdellah Salhi and Muhammad Sulaiman -- Chapter 19. Matheuristics for the Temporal Bin Packing Problem -- by Fabio Furini and Xueying Shen -- Chapter 20. A fast reoptimization approach for the dynamic technician routing and scheduling problem -- by V. Pillac, C. Guéret and A.L. Medaglia -- Chapter 21. Optimized air routes connections for real hub schedule using SMPSO Algorithm -- by H. Rahil, B. Abou El Majd and M. Bouchoum -- Chapter 22. Solving the P/Prec,pj;Ci j/Cmax using an evolutionary algorithm -- by Dalila Tayachi -- Chapter 23. A User Experiment on Interactive Reoptimization Using Iterated Local Search -- by David Meignan -- Chapter 24. Surrogate-Assisted Multiobjective Evolutionary Algorithm for Fuzzy Job Shop Problems -- by Juan Jose Palacios, Jorge Puente, Camino R. Vela, Inès Gonzalez-Rodriguez and El-Ghazali Talbi -- Chapter 25. Towards a novel reidentification method using metaheuristics -- by Tarik Ljouad, Aouatif Amine, Ayoub Al-Hamadi and Mohammed Rziza -- Chapter 26. Facing the feature selection problem with a binary PSO-GSA approach -- by Malek Sarhani, Abdellatif El Afia and Rdouan Faizi -- Chapter 27. An Optimal Deployment of Readers for RFID Network Planning using NSGA-II -- by Abdelkader Raghib, Badr Abou El Majd, and Brahim Aghezzaf -- Chapter 28. An Enhanced Bat Echolocation Approach for Security Audit Trails Analysis Using Manhattan Distance -- by Guendouzi Wassila and Boukra.
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.
Operations research.
Decision making.
Management science.
Computer science-Mathematics.
Operations Research/Decision Theory.
Operations Research, Management Science.
Math Applications in Computer Science.