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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 10 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
2006
Springer
181views Optimization» more  GECCO 2006»
15 years 10 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
121views Optimization» more  GECCO 2006»
15 years 10 months ago
A splicing/decomposable encoding and its novel operators for genetic algorithms
In this paper, we introduce a new genetic representation -- a splicing/decomposable (S/D) binary encoding, which was proposed based on some theoretical guidance and existing recom...
Yong Liang, Kwong-Sak Leung, Kin-Hong Lee
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 10 months ago
A dynamically constrained genetic algorithm for hardware-software partitioning
In this article, we describe the application of an enhanced genetic algorithm to the problem of hardware-software codesign. Starting from a source code written in a high-level lan...
Pierre-André Mudry, Guillaume Zufferey, Gia...
GECCO
2006
Springer
134views Optimization» more  GECCO 2006»
15 years 10 months ago
PSO and multi-funnel landscapes: how cooperation might limit exploration
Particle Swarm Optimization (PSO) is a population-based optimization method in which search points employ a cooperative strategy to move toward one another. In this paper we show ...
Andrew M. Sutton, Darrell Whitley, Monte Lunacek, ...