Speaker
Description
Genetic algorithms are search methods used in computing whose objective is to find exact or approximate solutions to optimization and search problems. A genetic algorithm mimics natural evolution, that is, it is based on optimizing a population (a subset of the entire search space). As in nature, the population consists of individuals that can reproduce and that can be affected by certain mutations, thus creating new individuals with better or worse properties than the previous ones. The goal of the algorithm is to direct the population towards creating better individuals, which can result in finding optimal solutions to a given problem.
In this talk, we will describe the use of a genetic algorithm for the construction of strongly regular graphs and directed strongly regular graphs from equitable partitions (i.e. orbit matrices) with a prescribed automorphism group.
