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Hardcover Recent Developments in Metaheuristics Book

ISBN: 3319582526

ISBN13: 9783319582528

Recent Developments in Metaheuristics

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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. Gu?ret 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, In?s 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.-

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