PROJECT PORTFOLIO SELECTION FROM A PRIORITY RANKING WITH SYNERGIC EFFECTS

Abstract

In this paper, a good portfolio is found through an ant colony algorithm (including a local search) that approximates the Pareto front regarding some kind of project categorization, cardinalities, synergy, discrepancies with priorities given by the ranking, and the average rank of supported projects; this approach is an improvement that includes synergy in the preferences model. The available information is only projects’ ranking and costs, a list of projects that are in synergy and usually, resource allocation follows the ranking priorities until they are depleted. The results show that our proposal obtains good results for different types of decision makers such as: conservative, strict or relaxed.