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» Solving Hierarchical Optimization Problems Using MOEAs
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83
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GECCO
2006
Springer
146views Optimization» more  GECCO 2006»
15 years 4 months ago
The dispersion metric and the CMA evolution strategy
An algorithm independent metric is introduced that measures the dispersion of a uniform random sample drawn from the top ranked percentiles of the search space. A low dispersion f...
Monte Lunacek, Darrell Whitley
81
Voted
WSC
1998
15 years 2 months ago
Adaptive Stochastic Manpower Scheduling
Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
Elmira Popova, David P. Morton
88
Voted
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
15 years 1 months ago
Experiments with indexed FOR-loops in genetic programming
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
Gayan Wijesinghe, Victor Ciesielski
86
Voted
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
15 years 1 months ago
Subheuristic search and scalability in a hyperheuristic
Our previous work has introduced a hyperheuristic (HH) approach based on Genetic Programming (GP). There, GP employs usergiven languages where domain-specific local heuristics ar...
Robert E. Keller, Riccardo Poli
133
Voted
AAECC
2007
Springer
117views Algorithms» more  AAECC 2007»
15 years 24 days ago
A predictor-corrector-type technique for the approximate parameterization of intersection curves
Abstract We describe a method to approximate a segment of the intersection curve of two implicitly defined surfaces by a rational parametric curve. Starting from an initial soluti...
Bert Jüttler, Pavel Chalmovianský