Data envelopment analysis (DEA) identifies an empirical efficient frontier of a set of peer decision making units (DMUs) with multiple inputs and outputs. The efficient frontier is characterized by the DMUs with an unity efficiency score. The performance of inefficient DMUs is characterized with respect to the identified efficient frontier. If the performance of inefficient DMUs deteriorates or...

In a recent publication, we presented a new multiobjective decision-making tool for use in conceptual engineering design. In the present paper, we provide important developments that support the next phase in the evolution of the tool. These developments, together with those of our previous work, provide a concept selection approach that capitalizes on the benefits of computational optimization...

The recently established diversity-multiplexing frontier characterizes the highSNR tradeoff between the best possible robustness and throughput gains obtainable by employing multiple antennas for digital communication in fading environments. We focus on the case of two transmit and at least two receive antennas, and show that a sufficient condition for a family of codebooks indexed by rate to a...

We compare, using data envelopment analysis (DEA), the performance of Islamic and conventional banks prior to, during and immediately after the 2008 financial crisis (2004-2009). There is no significant difference in mean efficiency between conventional and Islamic banks when efficiency is measured relative to a common frontier. A meta-frontier analysis (MFA), new to the banking context, howeve...