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GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
16 years 25 days ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
16 years 25 days ago
Self-modifying cartesian genetic programming
In nature, systems with enormous numbers of components (i.e. cells) are evolved from a relatively small genotype. It has not yet been demonstrated that artificial evolution is su...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
16 years 25 days ago
On the behavioral diversity of random programs
Generating a random sampling of program trees with specified function and terminal sets is the initial step of many program evolution systems. I present a theoretical and experim...
Moshe Looks
GECCO
2007
Springer
173views Optimization» more  GECCO 2007»
16 years 25 days ago
A hybrid GA for a supply chain production planning problem
The problem of production and delivery lot-sizing and scheduling of set of items in a two-echelon supply chain over a finite planning horizon is addressed in this paper. A single ...
Masoud Jenabi, S. Ali Torabi, S. Afshin Mansouri
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
16 years 25 days ago
Performance analysis of niching algorithms based on derandomized-ES variants
A survey of niching algorithms, based on 5 variants of derandomized Evolution Strategies (ES), is introduced. This set of niching algorithms, ranging from the very first derandom...
Ofer M. Shir, Thomas Bäck