This work proposes an heuristical approach based on evolutionary computation, whose goal is to find a set of minimum spanning trees in graphs that contain uncertainties in their parameters. This kind of problem is a NP-Hard one, because it involves an enormous number of comparisons. In order to avoid this complexity, this work proposes an artificial immune system that explores efficiently the search space of solutions to looking for satisfactory results, without the necessity of comparing all possible solutions.
evolutionary computation; fuzzy graphs; fuzzy mathematical programming
