Abstract. A two-population Genetic Algorithm for constrained optimization is exercised and analyzed. One population consists of feasible candidate solutions evolving toward optimal...
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two c...
A new evolutionary-progressive method for Multiple Sequence Alignment problem is proposed. The method efficiently combines flexibility of evolutionary approach with speed and accu...
To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To th...