2010 IEEE Congress on Evolutionary Computation Special Session on:
Niching Methods for Multimodal Optimization
Evolutionary Algorithms (EAs) in their original forms are usually designed for locating a single global solution. These algorithms typically converge to a single solution because of the global selection scheme used. Nevertheless, many real-world problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate many such satisfactory solutions so that a decision maker can choose one that is most proper in his/her problem domain. Numerous techniques have been developed in the past for locating multiple optima (global or local). These techniques are commonly referred to as “niching” methods. A niching method can be incorporated into a standard EA to promote and maintain formation of multiple stable subpopulations within a single population, with an aim to locate multiple globally optimal or suboptimal solutions. Many niching methods have been developed in the past, including crowding, fitness sharing, derating, restricted tournament selection, clearing, speciation, etc.
Most of existing niching methods, however, have difficulties which need to be overcome before they can be applied successfully to real-world multimodal problems. Some identified issues include: difficulties to pre-specify some niching parameters; difficulties in maintaining found solutions in a run; extra computational overhead; poor scalability when dimensionality is high. This special session aims to highlight the latest developments in niching methods, bring together researchers from academia and industries, and explore future research directions on this topic. We invite authors to submit original and unpublished work on niching methods. Topics of interest include but are not limited to:
Theoretical developments in multimodal optimization
Niching methods that incurs lower computational costs
Handling the issue of niching parameters in niching methods
Handling the scalability issue in niching methods
Handling problems characterized by massive multi-modality
Adaptive or parameter-less niching methods
Multiobjective approaches to niching
Multimodal optimization in dynamic environments
Niching methods applied to discrete multimodal optimization problems
Niching methods applied to constrained multimodal optimization problems
Niching methods using parallel or distributed computing techniques
Benchmarking niching methods, including test problem design and performance metrics
Comparative studies of various niching methods
Niching methods applied to engineering and other real-world multimodal optimization problems
Please note that we are NOT interested if the adopted task is to find a single solution of a multimodal problem.
Manuscripts should be prepared according to the standard format and page limit of regular papers specified in CEC2010 and submitted through the website http://www.wcci2010.org/. Special session papers will be treated in the same way as regular papers and included in the conference proceedings.
Paper Submission: 31 January 2010
Decision Notification: 15 March 2010
Final Camera-Ready Submission: 2 May 2010
Jeffrey Horn, Northern Michigan University, USA
Grant Dick, University of Otago, New Zealand
Jane Jing Liang, Zhengzhou University, China
Gulshan Singh, University of Texas at San Antonio, USA
Dipti Srinivasan, National University of Singapore, Singapore
Ami Moshaiov, Tel-Aviv University, Israel
Qingfu Zhang, University of Essex, UK
Andries Engelbrecht, University of Pretoria, South Africa
Alessandro Passaro, University of Pisa, Italy
More to be confirmed ...
Dr. Xiaodong Li
School of Computer Science and Information Technology
RMIT University
Melbourne, VIC 3001, Australia
Email: xiaodong.li@rmit.edu.au
Professor Kalyanmoy Deb
Deva Raj Chair Professor
Department of Mechanical Engineering
Indian Institute of Technology Kanpur
PIN 208016, India
Email: deb@iitk.ac.in
Dr. Ofer Shir
Postdoctoral Research Associate
Rabitz Group, Princeton University
Princeton, New Jersey, USA
Email: oshir@Princeton.EDU
Associate Professor P. N. Suganthan
School of Electrical and Electronic Engineering
Nanyang Technological University
Singapore, 639798
Email: epnsugan@ntu.edu.sg
Dr. Jian-Ping Li
School of Engineering, Design and Technology
Bradford University
Bradford, UK
Email: j.p.li@bradford.ac.uk