Optimization of energy supply systems: Simulated annealing versus genetic algorithm

摘要

We have applied two methods (simulated annealing and genetic algorithms) to search the solution of a problem of optimization with constraints in order to determine the best way to fulfill different energy demands using a set of facilities of energy transformation and storage. We have introduced a computational efficiency factor that measures the efficiency of the optimization algorithm and, as a result, we can conclude that for short computation times, genetic algorithms are more efficient than simulated annealing when demand profiles are not very long, whereas the latter is more efficient than the former for long computation time or for big demand profiles. [References: 18]