A Novel Binary Firefly Algorithm for the Minimum Labeling Spanning Tree Problem

Given a connected undirected graph G whose edges are labeled, the minimum labeling spanning tree (MLST) problem is to find a spanning tree of G with the smallest number of different labels. The MLST is an NP-hard combinatorial optimization problem, which is widely applied in communication networks, multimodal transportation networks, and data compression. Some approximation algorithms and heuristics algorithms have been proposed for the problem. Firefly algorithm is a new meta-heuristic algorithm. Because of its simplicity and easy implementation, it has been successfully applied in various fields. However, the basic firefly algorithm is not suitable for discrete problems. To this end, a novel discrete firefly algorithm for the MLST problem is proposed in this paper. A binary operation method to update firefly positions and a local feasible handling method are introduced, which correct unfeasible solutions, eliminate redundant labels, and make the algorithm more suitable for discrete problems. Computational results show that the algorithm has good performance. The algorithm can be extended to solve other discrete optimization problems.