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GECCO
2004
Springer
108views Optimization» more  GECCO 2004»
15 years 5 months ago
Simple Population Replacement Strategies for a Steady-State Multi-objective Evolutionary Algorithm
This paper explores some simple evolutionary strategies for an elitist, steady-state Pareto-based multi-objective evolutionary algorithm. The experimental framework is based on the...
Christine L. Mumford
97
Voted
GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
15 years 6 months ago
Understanding cooperative co-evolutionary dynamics via simple fitness landscapes
Cooperative co-evolution is often used to solve difficult optimization problems by means of problem decomposition. Its performance for such tasks can vary widely from good to disa...
Elena Popovici, Kenneth A. De Jong
IJIT
2004
15 years 1 months ago
Memetic Algorithm Based Path Planning for a Mobile Robot
In this paper, the problem of finding the optimal collision free path for a mobile robot, the path planning problem, is solved using an advanced evolutionary algorithm called memet...
Neda Shahidi, Hadi Esmaeilzadeh, Marziye Abdollahi...
192
Voted
UPP
2004
Springer
15 years 5 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
89
Voted
EVOW
2005
Springer
15 years 6 months ago
Self-Adapting Evolutionary Parameters: Encoding Aspects for Combinatorial Optimization Problems
Abstract. Evolutionary algorithms are powerful tools in search and optimization tasks with several applications in complex engineering problems. However, setting all associated par...
Marcos H. Maruo, Heitor S. Lopes, Myriam Regattier...