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GECCO
2005
Springer
288views Optimization» more  GECCO 2005»
15 years 11 months ago
A comparison study between genetic algorithms and bayesian optimize algorithms by novel indices
Genetic Algorithms (GAs) are a search and optimization technique based on the mechanism of evolution. Recently, another sort of population-based optimization method called Estimat...
Naoki Mori, Masayuki Takeda, Keinosuke Matsumoto
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 9 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
ATAL
2008
Springer
15 years 8 months ago
On k-optimal distributed constraint optimization algorithms: new bounds and algorithms
Distributed constraint optimization (DCOP) is a promising approach to coordination, scheduling and task allocation in multi agent networks. In large-scale or low-bandwidth network...
Emma Bowring, Jonathan P. Pearce, Christopher Port...
GECCO
2009
Springer
121views Optimization» more  GECCO 2009»
16 years 16 days ago
Evolutionary algorithms and dynamic programming
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled...
Benjamin Doerr, Anton Eremeev, Christian Horoba, F...
GECCO
2005
Springer
15 years 11 months ago
On the practical genetic algorithms
This paper offers practical design-guidelines for developing efficient genetic algorithms (GAs) to successfully solve realworld problems. As an important design component, a prac...
Chang Wook Ahn, Sanghoun Oh, Rudrapatna S. Ramakri...