META 2020 : Int. Conf. on Metaheuristics and Nature Inspired Computing

  in Conferences   Posted on January 24, 2020

Conference Information

Submission Deadline Friday 24 Apr 2020 Proceedings indexed by :
Conference Dates Oct 27, 2020 - Oct 31, 2020
Conference Address Marrakech, Morocco
Conference & Submission Link http://meta2020.sciencesconf.org
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers

META is one of the main event focusing on the progress of the area of metaheuristics and their applications. As in previous editions, META’2020 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.

All selected long papers will be published in the springer (SCOPUS, ISI, DBLP) conference proceedings.

At least, 2 special special issues in ISI and SCOPUS journals are also confirmed.

META\’2020 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\’2018 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’2020 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

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