Improving EA-based design space exploration by utilizing symbolic feasibility tests
Schlichter T, Haubelt C, Teich J (2005)
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2005
Pages Range: 1945-1952
Conference Proceedings Title: Proceedings of Genetic and Evolutionary Computation Conference (GECCO)
Event location: Washington, D.C.
ISBN: 1595930108
Abstract
This paper will propose a novel approach in combining Evolutionary Algorithms with symbolic techniques in order to improve the convergence of the algorithm in the presence of large search spaces containing only few feasible solutions. Such problems can be encountered in many real-world applications. Here, we will use the example of design space exploration of embedded systems to illustrate the benefits of our approach. The main idea is to integrate symbolic techniques into the Evolutionary Algorithm to guide the search towards the feasible region. We will present experimental results showing the advantages of our novel approach. Copyright 2005 ACM.
Authors with CRIS profile
Christian Haubelt
Technische Fakultät
Jürgen Teich
Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)
Related research project(s)
How to cite
APA:
Schlichter, T., Haubelt, C., & Teich, J. (2005). Improving EA-based design space exploration by utilizing symbolic feasibility tests. In Beyer H.G.; O'Reilly U.M.; Arnold D.; Banzhaf W.; Blum C.; Bonabeau E.W.; Cantu-Paz E.; Dasgupta D.; Deb K.; et al (Eds.), Proceedings of Genetic and Evolutionary Computation Conference (GECCO) (pp. 1945-1952). Washington, D.C., US.
MLA:
Schlichter, Thomas, Christian Haubelt, and Jürgen Teich. "Improving EA-based design space exploration by utilizing symbolic feasibility tests." Proceedings of the GECCO 2005 - Genetic and Evolutionary Computation Conference, Washington, D.C. Ed. Beyer H.G.; O'Reilly U.M.; Arnold D.; Banzhaf W.; Blum C.; Bonabeau E.W.; Cantu-Paz E.; Dasgupta D.; Deb K.; et al, 2005. 1945-1952.
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