The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent pop...
This paper extends an adaptive discretization method, Spliton-Demand (SoD), to be capable of handling multidimensional continuous search spaces. The proposed extension is called m...
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
This paper presents an architecture which is suitable for a massive parallelization of the compact genetic algorithm. The approach is scalable, has low synchronization costs, and i...
This paper presents an approach to combine competent crossover and mutation operators via probabilistic model building. Both operators are based on the probabilistic model buildin...
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm (cGA) to solve very large scale problems with millions to billions of va...
Kumara Sastry, David E. Goldberg, Xavier Llor&agra...