In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Genetic Algorithms (GAs) are very commonly used as function optimizers, basically due to their search capability. A number of different serial and parallel versions of GA exist. ...
In this paper, a novel approach for designing chromosome has been proposed to improve the effectiveness, which called multistage operation-based genetic algorithm (moGA). The obje...
Genetic algorithms (GAs) have long been used for large join query optimization (LJQO). Previous work takes all queries as based on one granularity to optimize GAs and compares the...
This paper presents a genetic algorithm (GA) with specialized encoding, initialization and local search genetic operators to optimize communication network topologies. This NPhard...