Hybrid Approaches based on Simulated Annealing, Tabu Search and Ant Colony Optimization for Solving the k-Minimum Spanning Tree Problem

In graph theory, the k-minimum spanning tree problem is considered to be one of the well-known NP hard problems to solve. This paper address this problem by proposing several hybrid approximate approaches based on the combination of simulated annealing, tabu search and ant colony optimization algorithms. The performances of the proposed methods are compared to other approaches from the literature using the same well-known library of benchmark instances.