9 search results - page 2 / 2 » Defining and Optimizing Indicator-Based Diversity Measures i... |
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
In the design of evolutionary multiobjective optimization (EMO) algorithms, it is important to strike a balance between diversity and convergence. Traditional mask-based crossover...
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
In multiobjective particle swarm optimization (MOPSO) methods, selecting the local best and the global best for each particle of the population has a great impact on the convergen...
CIDM
2009
IEEE
14 years 15 days ago
2009
IEEE
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
CEC
2010
IEEE
13 years 6 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 ...