Ricerc@Sapienza

In decision making processes in complex organizational contexts it is often insufficient to make a decision based on a single criterion and it is more realistic to consider different goals simultaneously, often in conflict with each other. An important class of multi-criteria problems is represented by the multi-objective combinatorial optimization problems, especially on networks, in which all or part of decision variables can assume only integer values and where the criteria and constraints that define the problem are expressed by linear functions. In this project we face a fundamental problem in this area: the bi-objective minimum spanning tree problem occurring in several applications and in particular in telecommunication (TLC) networks, where the spanning tree represents the topological structure ensuring connectivity among all nodes with minimum number of arcs. Currently, the TLC area is willing to adopt more sustainable (that is, less energy consuming) transmission networks (see for example [1], [2], [3], [4] and [5]), and, at best of our knowledge, in literature works modelling simultaneously two criteria (quality of the service and energy consumption) and where the whole Pareto frontier is explored, are not present. Our objective is to design and implement a new solution techniques for finding a complete set of Pareto optimal solutions. The algorithms will be tested on networks taken from real TLC environment.