DescriptionThis text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.
1. Parallel Branch-and-Bound Algorithms (T. Crainic, B. Lecun, C. Roucairol).
2. Parallel Dynamic Programming (F. Almeida, D. Gonzalez, I. Pelaez).
3. Parallel Branch and Cut (T. Ralphs).
4. Parallel Semidefinite Programming and Combinatorial Optimization (S. J. Benson).
5. Parallel Resolution of the Satisfiability Problem: A Survey (D. Singer).
6. Parallel Metaheuristics: Algorithms and Frameworks (N. Melab, E-G. Talbi, S. Cahon, E. Alba, G. Luque).
7. Towards Parallel Design of Hybrids between Metaheuristics and Exact Methods (M. Basseur, L. Jourdan, E-G. Talbi).
8. Parallel Exact Methods for Multiobjective Combinatorial Optimization (C. Dhaenens, J. Lemesre, N. Melab, M. Mezmaz, E-G. Talbi).
9. Parallel Primal-Dual Interior Point Methods for Semidefinite Programs (M. Yamashita, K. Fujisawa, M. Fukuda, M. Kojima, K. Nakata).
10. MW: A Software Framework for Combinatorial Optimization on Computational Grids (W. Glankwamdee, T. Linderoth).
11. Constraint Logic Programming on Multiple Processors (I. Sakellariou, I. Vlahavas).
12. Application of Parallel Metaheuristics to Optimization Problems in Telecommunications and Bioinformatics (S. L. Martins, C. Ribeiro, I. Rosseti).