Aim
Evolutionary computational methods play an important role in solving hard optimization problems from various real-world applications, such as scheduling, routing, constraint satisfaction, multi-objective optimization, time-varying, resource allocations, and many other areas. However, real-world optimizations are required to be more robust, more flexible, more responsive, more complex and more efficient. By solely using standard evolutionary computational methods, we may not reach the best solution within a limited time that is available for a real-world problem.To achieve better results, hybrid evolutionary computational methods need to be developed by mixing the mechanisms of different optimization methods or by modifying standard optimization methods such as stochastic methods, heuristic and metaheuristic methods, deterministic methods, and response surface methodology based approaches. Literature shows that recently developed hybrid evolutionary computational methods are usually able to obtain better solutions with smaller computational time than those obtained by the standard evolutionary algorithms.
This special session aims to attract academia and industry researchers to report the latest development of hybrid evolutionary computational methods for solving complex optimization problems, and finally raise awareness on the relevant issues related to such innovative optimization methods.
Scope
Relevant areas include (but are not limited to) the followings:- Methodology for development of hybrid evolutionary computational methods based on:
- New variants of deterministic, heuristic and stochastic optimization methods
- Hybridization of standard optimization methods and Metaheuristics
- Other heuristic algorithms such as particle swarm optimization, bee colony optimization, ant colony optimization, simulated annealing
- Parallel computing for complex optimization problems
- Continuous and discrete global or local optimization methods
- Multi-objective optimization methods
- Transformation of problem formulation space for optimization
- Time-varying optimization
- Application areas:
- Scheduling, resource allocation, graphs
- Routing, network communication
- Data mining, data processing, clustering
- Signal processing
- Supply chains, logistic problems
- Optimal control, system modeling
- Time series forecasting
- Other real world hard optimization problems
Deadline
The deadline for submissions to this special session is 20 December 2013.Information for Authors
1) Information on the format and templates for papers can be found here:http://www.ieee-wcci2014.org/Paper%20Submission.htm
2) Papers should be submitted via the IJCNN 2014 paper submission site:
http://ieee-cis.org/conferences/cec2014/upload.php)
Select the Special Session name in the Main Research topic dropdown list
4) Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of December 20, 2013
Organisers
1. Dr. Kit Yan ChanDepartment of Electrical and Computer Engineering, Curtin University, Australia
Email: kit.chan@curtin.edu.au
2. Dr. Vasile Palade
Department of Computer Science, University of Oxford, United Kingdom
Email: vasile.palade@cs.ox.ac.uk
3. Dr. Kevin Kam Fung Yuen
Department of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool University, China
Email: Kevin.Yuen@xjtlu.edu.cn
4. Associate Prof. Cedric Ka Fai Yiu
Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong
Email: macyiu@polyu.edu.hk
No comments:
Post a Comment
Note: only a member of this blog may post a comment.