Research Activity 3:

Learning genetic algorithms for a suite of problems in space science

Genetic algorithms are heuristic solutions that employ the principles of evolution found in nature to the finding of an optimal solution to a large variety of different problems. Based on a suitable computational setting, a suite of search techniques is employed to approach such optimization problems including randomness, population, mutation, crossover, and selection techniques. In space science related applications, genetic algorithms have been used to provide promising solutions to a broad range of problems such as galaxy collisions investigation, helioseismic investigations, solar coronal modeling, and classification of stars, among others.

To enhance the research capability in space science, and to introduce students to the conceptual model, and basic skills of developing genetic algorithm, the proposed research activity focuses on the development of a computer visualization/animation software package. The proposed software package will be developed to provide novel learning experiences of genetic algorithms solutions to space science related applications.