Section 2 succinctly introduces the directional distance function and further elaborates on the DSBM model detailing its properties.
Directional distance function is concisely presented in this section along with describing the DSBM model.
Relevant to this, the DSBM model of efficiency was introduced by Jahanshahloo et al.
Now, by selecting the direction vector g = (-[g.sup.-], [g.sup.+]) as [g.sub.i.sup.-] = [x.sub.io] (i= 1, ..., m), [g.sub.k.sup.+] = [y.sub.ko] (k = 1, ..., s), we consider the DSBM model by the following model which is a special case of the SBM  and the ERM 16] with respect to [T.sub.G]:
Likewise, the objective function of the DSBM model is responsible for increasing [[theta].sub.i] and [[phi].sub.k] (i = 1,..., m, k = 1, ..., s).
It is necessary to highlight that the DSBM model entails several favorable confidants which can be inferred as follows.
While the aviation 3M data accuracy has improved significantly in recent years, it still requires "cleaning up" before it can be used by the DSBM. Equally important, configuration anomalies must be addressed to ensure the configuration input into the model reflects the configuration desired by the FMS customer.
Also, an APML can use the DSBM to assess additional I-level repair capability and/or changes to I-level turn around time to take advantage of a particular regional repair capability existing within the proximity of potential FMS customers.