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GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
15 years 1 months ago
Particle swarm with speciation and adaptation in a dynamic environment
This paper describes an extension to a speciation-based particle swarm optimizer (SPSO) to improve performance in dynamic environments. The improved SPSO has adopted several prove...
Xiaodong Li, Jürgen Branke, Tim Blackwell
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 1 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 1 months ago
A combinatorial genetic algorithm for the configuration of the 2dF/AAOmega spectrograph at the anglo-Australian observatory
To help unravel the structure of the universe, astronomers have developed systems which observe large clusters of objects at the same time. One such system is the 2-degree field s...
Steven Manos, Geraint Lewis
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
15 years 1 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 1 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...