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EVOW
2003
Springer
15 years 7 months ago
GAME-HDL: Implementation of Evolutionary Algorithms Using Hardware Description Languages
Evolutionary Algorithms (EAs) have been proposed as a very powerful heuristic optimization technique to solve complex problems. Many case studies have shown that they work very eff...
Rolf Drechsler, Nicole Drechsler
EMO
2001
Springer
107views Optimization» more  EMO 2001»
15 years 6 months ago
Multi-objective Optimisation of Cancer Chemotherapy Using Evolutionary Algorithms
The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, t...
Andrei Petrovski, John A. W. McCall
GECCO
2004
Springer
15 years 7 months ago
Towards a Generally Applicable Self-Adapting Hybridization of Evolutionary Algorithms
When applied to real-world problems, the powerful optimization tool of Evolutionary Algorithms frequently turns out to be too time-consuming due to elaborate fitness calculations t...
Wilfried Jakob, Christian Blume, Georg Bretthauer
113
Voted
GECCO
1999
Springer
145views Optimization» more  GECCO 1999»
15 years 6 months ago
Three Ways to Grow Designs: A Comparison of Embryogenies for an Evolutionary Design Problem
This paper explores the use of growth processes, or embryogenies, to map genotypes to phenotypes within evolutionary systems. Following a summary of the significant features of em...
Peter J. Bentley, Sanjeev Kumar
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 8 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart