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» An evolutionary method for complex-process optimization
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74
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GECCO
2005
Springer
143views Optimization» more  GECCO 2005»
15 years 6 months ago
Niching in evolution strategies
Evolutionary Algorithms (EAs), popular search methods for solving search and optimization problems, are known for successful and fast location of single optimal solutions. However,...
Ofer M. Shir, Thomas Bäck
104
Voted
GECCO
2009
Springer
126views Optimization» more  GECCO 2009»
15 years 5 months ago
Improving NSGA-II with an adaptive mutation operator
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters pre...
Arthur Gonçalves Carvalho, Aluizio F. R. Ar...
80
Voted
GECCO
2005
Springer
163views Optimization» more  GECCO 2005»
15 years 6 months ago
Benefits of software measures for evolutionary white-box testing
White-box testing is an important method for the early detection of errors during software development. In this process test case generation plays a crucial role, defining appropr...
Frank Lammermann, Stefan Wappler
125
Voted
CEC
2009
IEEE
15 years 7 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
GECCO
2003
Springer
245views Optimization» more  GECCO 2003»
15 years 5 months ago
A Non-dominated Sorting Particle Swarm Optimizer for Multiobjective Optimization
Abstract. This paper introduces a modified PSO, Non-dominated Sorting Particle Swarm Optimizer (NSPSO), for better multiobjective optimization. NSPSO extends the basic form of PSO...
Xiaodong Li