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ISDA
2010
IEEE
15 years 4 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
16 years 1 months ago
Articulating user preferences in many-objective problems by sampling the weighted hypervolume
The hypervolume indicator has become popular in recent years both for performance assessment and to guide the search of evolutionary multiobjective optimizers. Two critical resear...
Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart...
EVOW
2007
Springer
15 years 10 months ago
Evaluation of Different Metaheuristics Solving the RND Problem
RND (Radio Network Design) is a Telecommunication problem consisting in covering a certain geographical area by using the smallest number of radio antennas achieving the biggest co...
Miguel A. Vega-Rodríguez, Juan Antonio G&oa...
SC
1995
ACM
15 years 10 months ago
Parallelizing the Phylogeny Problem
The problem of determining the evolutionary history of species in the form of phylogenetic trees is known as the phylogeny problem. We present a parallelization of the character c...
Jeff A. Jones, Katherine A. Yelick
GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
15 years 7 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...