In conjunction with the 11th Metaheuristics International Conference MIC'2015
7-10 June, 2015
Plenty of hard problems in a wide range of application areas, including engineering design, telecommunications, logistics, etc. have been modelled and tackled successfully with metaheuristics (evolutionary algorithms, scatter or swarm search, simulated annealing, Tabu search, etc.). Nowadays, optimization problems become increasingly large and complex, forcing the use of parallel computing for their efficient and effective resolution. On the other hand, parallel computing has recently undergone a significant evolution in terms of performance and energy consumption with the emergence of multi-core and many-core computing technologies (GPU, MIC, etc.). Indeed, accelerators and coprocessors have powered many parallel and/or distributed environements including high-performance workstations, hybrid clusters among them the top ranked Top500 and Green500 ones, and computational grids and clouds.