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Call for Papers Special Session on Evolutionary Algorithms in Forecasting Support Systems |
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Special Session Organizer Dr. Wei-Chiang Samuelson Hong Department of Information Management Oriental Institute of Technology, Taiwan Email: samuelhong@ieee.org Program Committee Prof. Steven Guan Prof. Lipo Wang School of Electrical & Electronic Engineering Nanyang Technological University, SG Email: elpwang@ntu.edu.sg Prof. Edward Tsang Prof. Pedro Isasi Prof. David Quintana Prof. Asunción Mochón Departamento de Economía Universidad Nacional de Educación a Distancia, Spain Email: amochon@cee.uned.es Prof. Pei-Chann Chang Department of Information Management
Yuan Ze
University,
Taiwan Prof. Takashi Washio Institute of Scientific & Industrial Research
Osaka
University, Japan Dr. Qingfu Zhang Department of Computer Science
University of Essex, UK Dr. Dietmar Maringer Centre for Computational Finance and Economic Agents (CCFEA) University of Essex, UK Email: dmaring@essex.ac.uk Dr. Wei-yu Kevin Chiang Prof. Ping-Feng Pai Department of Information Management
National Chi
Nan University, Taiwan Important Dates Paper Submission March 15, 2007 Decision Notification May 15, 2007 Camera-ready June 15, 2007 Conference September 25-28, 2007 |
Motivation Businesses require accurate forecasts of demand in order to make effective decisions, such as marketing, financial investment, inventory, distribution, human resource planning, purchasing, and so on. These forecasts are usually based on a function combination system (Forecasting support systems; FSS) of traditional statistical methods, evolutionary algorithms, artificial intelligent computation, and management judgment. Although the wide application of FSS concepts, due to lack of abilities to catch the forecast data pattern, FSS resulted in over-reliance on the use of informal judgment and higher expense. With the advantages of evolutionary algorithms computing capabilities over the traditional optimization approaches, recently, they have been applied to catch the data pattern more accurate via systematical computation process, such as genetic algorithms (GA), simulated annealing algorithms (SA), tabu search algorithms (TA), ant colony optimization (ACO), immune algorithm (IA), and particle swarm optimization algorithm (PSO). The objective of this special session is to invite together research and application of evolutionary algorithms for any forecasting fields. Topics This special session invites contributions in all aspects of applying evolutionary algorithms in any FSS to improve the usage efficiency of those algorithms and aims to promote the discussion and exploration of new ideas. Topics of interests include (but not limited to): v The usage of evolutionary algorithms in any FSS. v Theoretical comparison of evolutionary algorithms in FSS. v Empirical comparison of evolutionary algorithms in FSS. v Parameter determination by genetic algorithms (GA) in FSS. v Parameter determination by simulated annealing algorithms (SA) in FSS. v Parameter determination by tabu search algorithms (TA) in FSS. v Parameter determination by ant colony optimization (ACO) in FSS. v Parameter determination by immune algorithm (IA) in FSS. v Parameter determination by particle swarm optimization algorithm (PSO) in FSS. v Other application of novel intelligent evolutionary algorithms in FSS. Paper Submission Manuscripts should be prepared according to the standard format of regular papers specified in CEC2007 and be restricted to a maximum of 8 pages. Paper submission is strictly only PDF format and online through the regular CEC2007 submission website. Special session papers will be treated in the same way as regular papers and included in the conference proceedings. Notice The conference proceedings of CEC have been continuously included in the EI Compendex Database and IEEE Xplore. Sponsors Supported by
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Last revised: 5 October 2006 CopyRight © 2006-2007 All Rights Reserved. |
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