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» On Using Populations of Sets in Multiobjective Optimization
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GECCO
1999
Springer
15 years 1 months ago
Terrain-Based Genetic Algorithm (TBGA): Modeling Parameter Space as Terrain
The Terrain-Based Genetic Algorithm (TBGA) is a self-tuning version of the traditional Cellular Genetic Algorithm (CGA). In a TBGA, various combinations of parameter values appear...
V. Scott Gordon, Rebecca Pirie, Adam Wachter, Scot...
AE
2007
Springer
15 years 3 months ago
The Cooperative Royal Road: Avoiding Hitchhiking
We propose using the so called Royal Road functions as test functions for cooperative co-evolutionary algorithms (CCEAs). The Royal Road functions were created in the early 90’s ...
Gabriela Ochoa, Evelyne Lutton, Edmund K. Burke
GECCO
2009
Springer
145views Optimization» more  GECCO 2009»
15 years 2 months ago
Investigating and exploiting the bias of the weighted hypervolume to articulate user preferences
Optimizing the hypervolume indicator within evolutionary multiobjective optimizers has become popular in the last years. Recently, the indicator has been generalized to the weight...
Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart...
GECCO
2007
Springer
157views Optimization» more  GECCO 2007»
15 years 3 months ago
A doubly distributed genetic algorithm for network coding
We present a genetic algorithm which is distributed in two novel ways: along genotype and temporal axes. Our algorithm first distributes, for every member of the population, a su...
Minkyu Kim, Varun Aggarwal, Una-May O'Reilly, Muri...
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GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
15 years 3 months ago
Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the perf...
Kagan Tumer, Adrian K. Agogino