|
|
|
| |||||||||||||||
META 2016 : META'2016 Int. Conf. on Metaheuristics and Nature Inspired Computing | |||||||||||||||
| Link: http://meta2016.sciencesconf.org | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
|
**********************************************************************
META'2016 International Conference on Metaheuristics and Nature Inspired Computing 27-31 Oct 2016 Marrakech, Morocco http://meta2016.sciencesconf.org/ ********************************************************************** META is one of the main event focusing on the progress of the area of metaheuristics and their applications. As in previous editions, META’2016 will provide an opportunity to the international research community in metaheuristics to discuss recent research results, to develop new ideas and collaborations, and to meet old friends and make new ones in a friendly and relaxed atmosphere. META'2016 welcomes presentations that cover any aspects of metaheuristic research such as new algorithmic developments, high-impact applications, new research challenges, theoretical developments, implementation issues, and in-depth experimental studies. META'2016 strives for a high-quality program that will be completed by a number of invited talks, tutorials, workshops and special sessions. The scope of the META’2016 conference includes, but is not limited to: * Local search, tabu search, simulated annealing, VNS, ILS, … * Evolutionary algorithms, swarm optimization, scatter search, … * Emergent nature inspired algorithms: quantum computing, artificial immune systems, bee colony, DNA computing, … * Parallel algorithms * Hybrid methods with machine learning, game theory, mathematical programming, constraint programming, co-evolutionary, … * Application to: logistics and transportation, networks, scheduling, data mining, engineering design, energy, cloud, bio-medical, … * Theory of metaheuristics, landscape analysis, convergence, problem difficulty, very large neighbourhoods, … * Multi-objective optimization, bi-level optimization * Dynamic optimization, problems with uncertainty, … * Parameter tuning (static, dynamic, adaptive, self-adaptive) * Hyper-heuristics, cross-domain metaheuristics * Software frameworks for metaheuristics and nature inspired computing |
|
