Axial solutions for multiple objective linear problems. An application to target setting in DEA models with preferences

In this paper we introduce the class of axial solutions for multiple objective optimization problems in contexts in which partial information on preference weights is available. These solutions combine the use of an improvement axis to direct the search of the most preferred result with the concept of efficiency with respect to preference information. In addition, we show how this solution is used in data envelopment analysis in order to set realistic targets in accordance with either the partially specified preferences of a single decision maker, or the different individual preference information provided by the members of a group of decision makers.