An Application of Parallel Genetic Algorithms to Structure Determination of Surface Materials
Genetic algorithms model biological evolution to solve a variety computational problems. We investigated enhancements to the traditional genetic algorithm suited for difficult global optimization problems, including the use of parallel computers to speedup the execution and improve the quality of solution. Based on our studies, we designed a configurable, parallel genetic algorithm package that offers the choice of three parallel genetic algorithm models: global, island, and neighborhood. We configured and applied a parallel genetic algorithm to a difficult global optimization problem from the field of material science: structure determination from Low Energy Electron Diffraction experiments.