An Ant Colony Algorithm For Solving The Selection Portfolio Problem, Using A Quality-Assessment Model For Portfolios Of Projects Expressed By A Priority Ranking

One of the most important problems faced by any organization is make decisions about how to invest and manage the resources to get more benefits; however, the organizations resources are not enough to support all portfolios proposals. To these problems that face the executives of the big organizations, is known as Select Portfolio Problem. In this work is developed an ant colony algorithm, which is an especially effective meta-heuristic, this meta-heuristic is hybridized with a multi-objective local search, this strategy allows using knowledge of the ant, to build potential solutions, knowledge is obtained through the pheromone trail left by ants when find good solutions, for that the algorithm does not converge prematurely an evaporation strategy is implemented. The strategy meta-heuristic include an optimization model for portfolio selection called discrepancies model, this model is implemented when the information concerned to the quality of the projects is in form of ranking, besides help to evaluate portfolios through ten criteria to maximize the impact of the portfolio. This approach allowed reaching privileged areas of Pareto's front, where identified solutions that reflect the preferences of the decision maker. The experimental tests show the advantages of our proposal, providing reasonable evidence of its potential for solving the select portfolio problems with many objectives.