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GECCO
2003
Springer
118views Optimization» more  GECCO 2003»
15 years 3 months ago
Distributed Probabilistic Model-Building Genetic Algorithm
In this paper, a new model of Probabilistic Model-Building Genetic Algorithms (PMBGAs), Distributed PMBGA (DPMBGA), is proposed. In the DPMBGA, the correlation among the design var...
Tomoyuki Hiroyasu, Mitsunori Miki, Masaki Sano, Hi...
GECCO
2003
Springer
114views Optimization» more  GECCO 2003»
15 years 3 months ago
Learning the Ideal Evaluation Function
Abstract. Designing an adequate fitness function requiressubstantial knowledge of a problem and of features that indicate progress towards a solution. Coevolution takes the human ...
Edwin D. de Jong, Jordan B. Pollack
GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
15 years 2 months ago
Variable size population for dynamic optimization with genetic programming
A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. pro...
Leonardo Vanneschi, Giuseppe Cuccu
76
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HM
2009
Springer
145views Optimization» more  HM 2009»
15 years 2 months ago
A Hybrid Solver for Large Neighborhood Search: Mixing Gecode and EasyLocal + +
We present a hybrid solver (called GELATO) that exploits the potentiality of a Constraint Programming (CP) environment (Gecode) and of a Local Search (LS) framework (EasyLocal++ )....
Raffaele Cipriano, Luca Di Gaspero, Agostino Dovie...
CP
2000
Springer
15 years 2 months ago
Analysis of Random Noise and Random Walk Algorithms
Random Noise and Random Walk algorithms are local search strategies that have been used for the problem of satisfiability testing (SAT). We present a Markov-chain based analysis o...
Bhaskar Krishnamachari, Xi Xie, Bart Selman, Steph...