Dynamic and Static Simulated Annealing for Solving the Multi-objective K-Minimum Spanning Tree Problem

This paper deals with the optimisation of the Multi-Objectif k-Minimum Spanning Tree (MO k-MST) problem. A wide varieties of decision making problems in the real world can be formulated as a MO k-MST, which is known to be NP-complete. In order to solve a such problem, we propose two approximate approaches based on simulated annealing method: the first one will integrates the static weighted sum method while the second one uses the dynamic weighted sum method. Computational experiments were carried out in order to compare the performance of each method.