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GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 8 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
GECCO
2006
Springer
164views Optimization» more  GECCO 2006»
13 years 11 months ago
Adaptation for parallel memetic algorithm based on population entropy
In this paper, we propose the island model parallel memetic algorithm with diversity-based dynamic adaptive strategy (PMADLS) for controlling the local search frequency and demons...
Jing Tang, Meng-Hiot Lim, Yew-Soon Ong
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
EVOW
2007
Springer
14 years 1 months ago
An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA)...
Ferrante Neri, Niko Kotilainen, Mikko Vapa
ARCS
2007
Springer
13 years 11 months ago
Toward Self-adaptive Embedded Systems: Multi-objective Hardware Evolution
Abstract. Evolutionary hardware design reveals the potential to provide autonomous systems with self-adaptation properties. We first outline an architectural concept for an intrins...
Paul Kaufmann, Marco Platzner