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» On the Brittleness of Evolutionary Algorithms
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GECCO
2008
Springer
156views Optimization» more  GECCO 2008»
15 years 7 months ago
Computing minimum cuts by randomized search heuristics
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...
Frank Neumann, Joachim Reichel, Martin Skutella
CEC
2005
IEEE
15 years 11 months ago
Real-parameter optimization using the mutation step co-evolution
Abstract- An evolutionary algorithm for the optimization of a function with real parameters is described in this paper. It uses a cooperative co-evolution to breed and reproduce su...
Petr Posik
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
16 years 10 days 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
GECCO
2005
Springer
127views Optimization» more  GECCO 2005»
15 years 11 months ago
Evolutionary form-finding of tensegrity structures
Tensegrity structures are stable 3-dimensional mechanical structures which maintain their form due to an intricate balance of forces between disjoint rigid elements and continuous...
Chandana Paul, Hod Lipson, Francisco J. Valero Cue...
CCECE
2006
IEEE
16 years 7 days ago
New Constraints on Generation of Uniform Random Samples from Evolutionary Trees
In this paper, we introduce new algorithms for selecting taxon samples from large evolutionary trees, maintaining uniformity and randomness, under certain new constraints on the t...
Anupam Bhattacharjee, Zalia Shams, Kazi Zakia Sult...