Objective
INGENET NETWORK OVERVIEW
The increasing complexity of design in Aeronautic, Automotive and Energy Industries requires more and more robust optimisation and control tools for solving simultaneously discrete, continuous and combinatorial difficult problems unresolved until now. Evolutionary Algorithms (EAs) are artificial intelligence techniques which mimic nature according to the survival of the fittest Darwin s principle. They randomly encode physical (quantitative or qualitative) variables via digital DNA inside computers and are known for their robustness to better explore search spaces and find near-global optima than traditional optimisation methods. For this reason Evolutionary Algorithms are becoming widely used in many engineering and sciences problems. The main goal of the INGENET Network is to bring together academic and industrial partners in order to evaluate and compare performances of recent evolution based methodologies and (parallel) softwares on selected test problems of industrial interest.
The Network includes the following tasks:
- specifying its main objectives and activities, with reference to the exploratory phase;
- coordinating innovative industrial research on Evolutionary Algorithms;
- updating continuously the electronic INGENET Home Page Newsletter on the World Wide WEB dealing with genetic information relevant to industrial applications;
- installing an on going INGENET Database at INRIA Sophia Antipolis;
- computing selected model and industry oriented test cases;
- organizing once a year in Europe (the first in the Series scheduled in March 1998) a series of two-day Database Workshops bringing together node-partners to present, analyse, validate and synthesize electronic results of computation and innovative methodologies;
- organising a EUROGEN Short Course in Europe every two years presenting the State of the Art of theoretical, numerical and applicational aspects of Evolutionary Algorithms (the second in the Series entitled EUROGEN 97 to take place in Italy in 1997), seminars and training during review meetings once a year focused on theoretical aspects of EAs.
Fluids Dynamics, Acoustics, Structure Mechanics, Electromagnetics, Automation control and Energy are the featured multidisciplinary areas in Engineering and Applied Sciences targeted by INGENET where evolution approaches work impressively well. The ultimate goal of INGENET is to stimulate and disseminate widely and electronically in Europe innovative evolution based methodologies and software, providing a interactive dynamic bridge between Artificial Intelligence, Computer Sciences and Engineering for solving real life problems.
EUROPEAN DIMENSION AND PARTNERSHIP
The objective of the INGENET project is to set up a network of expertise in the field of Evolutionary Algorithms allowing Universities, Laboratories and Industries to collaborate in the development and validation of methodologies involving EAS as well as offering a benchmark platform for applications of industrial interest. The INGENET network intends to tandem node partners from Academy and Industry with the INGENET kernel. Industrial nodes will participate into the definition of test cases and their computations with Evolutionary Algorithms. They will participate during workshops in data evaluation and interpretation, giving views on the results from an industrial perspective. They will work in tandem with one or several universities or institutes of their choice to favour stimulation between teams and encourage the cross fertilization of evolution methodologies with the industrial environment. The interest of Universities and Research Institutes to participate in INGENET consists mainly in using Evolutionary Algorithms (EAs) in practical industrial applications in order to highlight the particular strength of these optimisation algorithms. As an outcome of INGENET these academic centres will get into contact with European industries or SMEs represented in INGENET to look for potential applications of EAs beyond the test cases discussed in the network.
POTENTIAL APPLICATIONS
This new optimisation technology was initially developed in the United States. Nowadays industrial problems require these global optimisation techniques and there is an increasing interest in Industry to apply these robust algorithms to their complex multi-objective multi-disciplinary design and control problems.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- natural sciences biological sciences genetics DNA
- natural sciences physical sciences classical mechanics fluid mechanics fluid dynamics
- natural sciences physical sciences acoustics
- natural sciences computer and information sciences internet world wide web
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Coordinator
92552 SAINT CLOUD
France
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