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» An informed convergence accelerator for evolutionary multiob...
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CEC
2011
IEEE
12 years 4 months ago
Accelerating convergence towards the optimal pareto front
—Evolutionary algorithms have been very popular optimization methods for a wide variety of applications. However, in spite of their advantages, their computational cost is still ...
Mohsen Davarynejad, Jafar Rezaei, Jos L. M. Vranck...
GECCO
2006
Springer
172views Optimization» more  GECCO 2006»
13 years 8 months ago
Multi-objective optimisation of the protein-ligand docking problem in drug discovery
The pharmaceutical industry is facing an ever-increasing demand to discover novel drugs that are more effective and safer than existing ones. The industry faces huge problem in im...
A. Oduguwa, A. Tiwari, S. Fiorentino, R. Roy
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
13 years 11 months ago
Informative performance metrics for dynamic optimisation problems
Existing metrics for dynamic optimisation are designed primarily to rate an algorithm’s overall performance. These metrics show whether one algorithm is better than another, but...
Stefan Bird, Xiaodong Li
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 8 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
13 years 10 months ago
Inverse multi-objective robust evolutionary design optimization in the presence of uncertainty
In many real-world design problems, uncertainties are often present and practically impossible to avoid. Many existing works on Evolutionary Algorithm (EA) for handling uncertaint...
Dudy Lim, Yew-Soon Ong, Bu-Sung Lee