Bio-inspired Algorithms for Continuous Parameter Optimisation
Due to a large number of request for late submissions, the EvoStar submission sites will stay open until this Tuesday 15 November 23:59:59 SST, after which no further submissions will be accepted. Authors who have already submitted, can update their work until this time.
The recipients of the "EvoAPPLICATIONS Best Paper Awards" will be
invited to submit an extended version of their works to a special
issue of Memetic Computing.
''The main application areas of EC techniques [in industry] are multi-objective optimization, classification, data mining and numerical optimization''. 
Many engineering problems of both theoretical and practical interest involve choosing the best configuration of a set of parameters to achieve a specified objective. Numerical optimisation refers to the case when these parameters take continuous real values, as opposed to combinatorial optimisation, which deals with discrete values. Examples include designing production processes for maximum efficiency, optimal parameter adjustment for controllers and many others. EvoNUM focuses on such problems.
We seek high quality papers involving the application of bio-inspired algorithms (genetic algorithms, genetic programming, evolution strategies, differential evolution, particle swarm optimization, evolutionary programming, simulated annealing and their hybrids) to continuous optimisation problems in engineering. We also welcome cross-fertilisation between Nature-inspired algorithms and more classical numerical optimisation algorithms.
 GS Hornby and T Yu, "EC Practitioners: Results of the First Survey", SIGEVOlution, Newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation, Vol. 2(1), Spring 2007 www.sigevolution.org
Areas of Interest and Contributions
deals with engineering applications where continuous parameters or functions have to be optimised, in fields such as control, chemistry, agriculture, electricity, building and construction, energy, aerospace engineering, design optimisation, etc.
aims to cover areas that include but are not limited to:
- Local learning of parameters
- Mechanisms to incorporate constraints
- Theoretical developments
- Performance measures and performance analysis
- Benchmark problems
Accepted papers will appear in the proceedings of EvoStar, published in a volume of the Springer Lecture Notes in Computer Science, which will be available at the Conference.Submissions must be original and not published elsewhere. The submissions will be peer reviewed by at least three members of the program committee. The authors of accepted papers will have to improve their paper on the basis of the reviewers comments and will be asked to send a camera ready version of their manuscripts. At least one author of each accepted work has to register for the conference and attend the conference and present the work.The reviewing process will be double-blind, please omit information about the authors in the submitted paper.
Submissions must be original and not published elsewhere. They will be peer reviewed by members of the program committee. The reviewing process will be double-blind, so please omit information about the authors in the submitted paper.
Submit your manuscript in Springer LNCS format.
Please provide up to five keywords in your Abstract
Page limit: 16 pages
Further information on the conference and co-located events can be
found in: http://www.evostar.org
EvoNUM track chair
- Anna I Esparcia-Alcázar
Universitat Politècnica de València, Spain
- Hans-Georg Beyer, Vorarlberg University of Applied Sciences, Austria
- Şima Etaner-Uyar, Istanbul Technical University, Turkey
- Bill Langdon, University College London, UK
- JJ Merelo, Universidad de Granada, Spain
- Boris Naujoks, TH - Köln University of Applied Sciences, Germany
- Ferrante Neri, De Montfort University, UK
- Petr Pošík, Czech Technical University in Prague, Czech Republic
- Mike Preuss, WWU Münster, Germany
- Guenter Rudolph, University of Dortmund, Germany
- Ivo Fabian Sbalzarini, Max Planck Institute of Molecular Cell Biology and Genetics, Germany
- Ke Tang, University of Science and Technology of China (USTC), China