Immune-inspired algorithm to find the set of κ-spanning trees with lowest costs in graphs with fuzzy parameters

In this work, we present an immune-inspired algorithm based on evolutionary computation to find the set of k-spanning trees with lowest costs in graphs with uncertainties in their parameters. In order to avoid the high complexity of the traditional approaches, we present an artificial immune system for exploring the search space looking for satisfactory results, without the necessity of comparing all possible solutions.