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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 1 months ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
Oliver Kramer, Bartek Gloger, Andreas Goebels
EVOW
2009
Springer
14 years 2 months ago
Discrete Particle Swarm Optimization for Multiple Destination Routing Problems
This paper proposes a discrete particle swarm optimization (DPSO) to solve the multiple destination routing (MDR) problems. The problem has been proven to be NP-complete and the tr...
Zhi-hui Zhan, Jun Zhang
ANTSW
2006
Springer
13 years 11 months ago
Applying Aspects of Multi-robot Search to Particle Swarm Optimization
Abstract. We present a modified version of the Particle swarm Optimization algorithm in which we adjust the virtual swarm search by incorporating inter-agent dynamics native to mul...
Jim Pugh, Loïc Segapelli, Alcherio Martinoli
ECAL
2003
Springer
14 years 24 days ago
Evolving Aggregation Behaviors in a Swarm of Robots
In this paper, we study aggregation in a swarm of simple robots, called s-bots, having the capability to self-organize and selfassemble to form a robotic system, called a swarm-bot...
Vito Trianni, Roderich Groß, Thomas Halva La...
ACCV
2009
Springer
14 years 2 months ago
A Smarter Particle Filter
Particle filtering is an effective sequential Monte Carlo approach to solve the recursive Bayesian filtering problem in non-linear and non-Gaussian systems. The algorithm is base...
Xiaoqin Zhang, Weiming Hu, Steve J. Maybank