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CEC
2010
IEEE
13 years 6 months ago
A novel hybrid evolutionary strategy and its periodization with multi-objective genetic optimizers
— This work investigates the effects of the periodization of local and global multi-objective search algorithms. To this, we introduce a model for periodization and define a new...
Paul Kaufmann, Tobias Knieper, Marco Platzner
GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
14 years 1 months ago
Hybridizing evolutionary algorithms and clustering algorithms to find source-code clones
This paper presents a hybrid approach to detect source-code clones that combines evolutionary algorithms and clustering. A case-study is conducted on a small C++ code base. The pr...
Andrew Sutton, Huzefa H. Kagdi, Jonathan I. Maleti...
ASC
2011
13 years 2 months ago
Quality of Service constrained routing optimization using Evolutionary Computation
In this work, a novel optimization framework is proposed that allows the improvement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of ...
Miguel Rocha, Pedro Sousa, Paulo Cortez, Miguel Ri...
AIPS
2006
13 years 9 months ago
Optimal STRIPS Planning by Maximum Satisfiability and Accumulative Learning
Planning as satisfiability (SAT-Plan) is one of the best approaches to optimal planning, which has been shown effective on problems in many different domains. However, the potenti...
Zhao Xing, Yixin Chen, Weixiong Zhang
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...