Identification of decision strategies in distribution planning

Distribution planning is a decision exercise based on future estimation of external noncontrollable data. Several criteria must be taken into account, in order to achieve solutions that are socio-economically adapted. Knowledge associated to future events is normally vague and nonsupported in statistical data introducing risk in any solution for the problem. The framework for the problem is a multicriteria one leading to nondominated solutions. Due to the typical size of the problem the results are normally characterized by a great number of solutions that make the decision even more difficult. In this contribution the author presents a strategy, able to help the decision maker to decide in an environment that takes explicitly into account the different criteria involved, as well as the uncertainties and risk associated. The strategy supports on a fuzzy clustering analysis able to identify decision strategies representative of the great number of possible solutions