Evolutionary Algorithms for Finding the k Most Vital Arcs in Minimum Spanning Tree Problem

The purpose of this study is to present methods for determining the k most vital arcs (k-MVAs) in the minimum spanning tree problem(MSTP) using evolutionary algorithms. The problem of finding the k-MVAs in MSTP is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the total length of minimum spanning tree. Generally, the problem which determine the k-MVAs in MSTP has known as NP-hard. Therefore, in order to deal with the problem of real world the heuristic algorithms are needed. In this study we propose to three genetic algorithms as the heuristic methods for finding the k-MVAs in MSTP. The algorithms to be presented in this study are developed using the library of the evolutionary algorithm framework(EAF) and the performance of the algorithms are analyzed through the computer experiment.