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EMO
2005
Springer
110views Optimization» more  EMO 2005»
13 years 10 months ago
Parallelization of Multi-objective Evolutionary Algorithms Using Clustering Algorithms
Abstract. While Single-Objective Evolutionary Algorithms (EAs) parallelization schemes are both well established and easy to implement, this is not the case for Multi-Objective Evo...
Felix Streichert, Holger Ulmer, Andreas Zell
PPSN
2010
Springer
13 years 3 months ago
Privacy-Preserving Multi-Objective Evolutionary Algorithms
Existing privacy-preserving evolutionary algorithms are limited to specific problems securing only cost function evaluation. This lack of functionality and security prevents thei...
Daniel Funke, Florian Kerschbaum
DMIN
2006
142views Data Mining» more  DMIN 2006»
13 years 6 months ago
Parallel Hybrid Clustering using Genetic Programming and Multi-Objective Fitness with Density (PYRAMID)
Clustering is the process of locating patterns in large data sets. It is an active research area that provides value to scientific as well as business applications. Practical clust...
Junping Sun, William Sverdlik, Samir Tout
PPSN
2010
Springer
13 years 3 months ago
Optimizing Delivery Time in Multi-Objective Vehicle Routing Problems with Time Windows
The Vehicle Routing Problem with Time Windows involves finding the lowest-cost set of routes to deliver goods to customers, which have service time windows, using a homogeneous ...
Abel Garcia-Najera, John A. Bullinaria
AIR
2002
165views more  AIR 2002»
13 years 4 months ago
Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons
The rapid advances of evolutionary methods for multi-objective (MO) optimization poses the difficulty of keeping track of the developments in this field as well as selecting an app...
Kay Chen Tan, Tong Heng Lee, Eik Fun Khor