Determining the Best Performance Time Period of a System

The main purpose of this paper is to determine the best performance time period of a system, consisting some DMUs, among some sequential time periods. This aim is satised by two proposed algorithms, the rst based on global Malmquist Productivity Index and the second is based on PPS frontiers

An interactive algorithm for multiobjective ranking for underlying linear and quasiconcave value functions

We develop interactive algorithms to find a strict total order for a set of discrete alternatives for two different value functions: linear and quasiconcave. The algorithms first construct a preference matrix and then find a strict total order. Based on the ordering, they select a meaningful pair of alternatives to present the decision maker (DM) for comparison. We employ methods to find all implied preferences of the DM, after he or she makes a preference. Considering all the preferences of the DM, the preference matrix is updated and a new strict total order is obtained until the termination conditions are met. We test the algorithms on several instances. The algorithms show fast convergence to the exact total order for both value functions, and eliciting preference information progressively proves to be efficient.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/168298/1/itor12704_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/168298/2/itor12704.pd