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GECCO
2007
Springer
191views Optimization» more  GECCO 2007»
13 years 11 months ago
An artificial immune system with partially specified antibodies
Artificial Immune System algorithms use antibodies which fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully spec...
Ramin Halavati, Saeed Bagheri Shouraki, Mojdeh Jal...
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
13 years 11 months ago
COSMO: a correlation sensitive mutation operator for multi-objective optimization
This contribution is the first to discover exploitable structural features within circuit optimization problems (COP) and discuss how it is indicative of a general structure and ...
Varun Aggarwal, Una-May O'Reilly
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
13 years 11 months ago
Distribution replacement: how survival of the worst can out perform survival of the fittest
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Howard Tripp, Phil Palmer
GECCO
2007
Springer
190views Optimization» more  GECCO 2007»
13 years 11 months ago
Analysis of evolutionary algorithms for the longest common subsequence problem
In the longest common subsequence problem the task is to find the longest sequence of letters that can be found as subsequence in all members of a given finite set of sequences....
Thomas Jansen, Dennis Weyland
GECCO
2007
Springer
157views Optimization» more  GECCO 2007»
13 years 11 months ago
Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover
Multiobjective optimization problems with many local Pareto fronts is a big challenge to evolutionary algorithms. In this paper, two operators, biased initialization and biased cr...
Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sen...
GECCO
2007
Springer
437views Optimization» more  GECCO 2007»
13 years 11 months ago
A gestalt genetic algorithm: less details for better search
The basic idea to defend in this paper is that an adequate perception of the search space, sacrificing most of the precision, can paradoxically accelerate the discovery of the mo...
Christophe Philemotte, Hugues Bersini
GECCO
2007
Springer
199views Optimization» more  GECCO 2007»
13 years 11 months ago
Multi-objective particle swarm optimization on computer grids
Abstract. In recent years, a number of authors have successfully extended particle swarm optimization to problem domains with multiple objectives. This paper addresses the issue of...
Sanaz Mostaghim, Jürgen Branke, Hartmut Schme...
GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
13 years 11 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles