IEEE Task Force on LSGO

SCI2S MIDAS

Objectives

The objectives of this task force are:

  • to promote the research and development of evolutionary computation techniques for large scale optimization problems.

  • to facilitate the knowledge sharing and collaboration between researchers in the related areas. There are many people, from Computer Science, Engineering, Math, Operation Research, etc., interested in large scale global optimization. But they are scattered in different places and in different conferences. One of the major aims of this TF is to provide a common forum for all these people to come together and exchange ideas. ECTC is ideally positioned to attract all these people and provide a home to these distributed groupings in different communities (from CS to Math and from OR to Engineering).

  • to exchange experience and promote discussion and contacts between researchers, industrialists and practitioners. The TF will actively recruit and engage industrialists and practitioners in its activities. In particular, the TF will solicit "grand challenges" in large scale global optimization, especially from industrialists and practitioners. Such "grand challenges" will then be put on the web to promote research into novel techniques for tackling such challenges. The existing infrastructure at the University of Birmingham can be used for such purpose:
    EvoCoBR: http://www.cs.bham.ac.uk/research/projects/ecb/

Anticipated interests

Evolutionary computation for large scale optimization is an inter-disciplinary topic that is closely related to parallelization of EAs, coevolution, EC assisted with meta-models, etc. Specifically, the anticipated interest of the proposed task force includes:
  • EC for large scale single objective numerical optimization, where the problem involves a large number of decision variables.

  • EC for large scale combinatorial optimization, such as the Traveling Salesman Problem (TSP), Vehicle/Arc Routing Problem (VRP/ARP), scheduling problem and etc.

  • EC for large scale multi-objective optimization. In the context of MO, the term "large scale" may refer to either large number of decision variables or objectives, or both.

  • Application of large scale EC techniques in challenging real-world problems.

Proposed activities

  • Organize workshops (e.g., IEEE Symp.)
  • Organize special sessions at international conferences (e.g., CEC)
  • Organize journal special issues

Chair

Daniel Molina (Chair)
University of Cadiz, Spain

Antonio LaTorre (Vice chair)
Universidad Politécnica de Madrid, Spain

Swagatam Das (Vice chair)
Indian Statistical Institute, India

Members

Ke Tang (University of Science and Technology of China, China) (Founding chair)
Xiaodong Li (Chair from 2012 - 2015)
Xin Yao (University of Birmingham, U.K.)
P. N. Suganthan (Nanyang Technological University, Singapore)
Ferrante Neri (University of Jyväskylä, Finland)
Janez Brest ( University of Maribor, Slovenia)
Kai Qin (University of Waterloo, Canada)
Manuel Lozano (University of Granada, Spain)
Zhenyu Yang (National University of Defense Technology, China)
Yew-soon Ong (Nanyang Technological University, Singapore)
Thomas Stützle (Université Libre de Bruxelles, Belgium)
Bin Li (University of Science and Technology of China, China)
Thomas Bäck (Leiden University, Netherlands)
Anikó Ekárt (Aston University, U.K.)
Maoguo Gong (Xidian University, China)
Yuping Wang (Xidian University, China)
Hui Li (Xi'an Jiaotong University, China)
Shahryar Rahnamayan (University of Ontario, Canada)
Mohammad Nabi Omidvar (University of Birmingham, UK)

Contact us

If you have any suggestions for this task force, please contact: Daniel Molina: daniel.molina@uca.es