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GECCO
2008
Springer
13 years 8 months ago
2008
Springer
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
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...
EMO
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...
CEC
2010
IEEE
13 years 8 months ago
2010
IEEE
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...
GECCO
2003
Springer
14 years 7 days ago
2003
Springer
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-mo...