Before solving the suboptimization
method, we must ensure that the number of rows is greater than the number of columns in the candidate atomic matrix [mathematical expression not reproducible]; that is, [mathematical expression not reproducible] is a full column-rank matrix.
This is because it requires solving suboptimization
problems to calibrate the AL of the sub-preferred routes.
From Lemmas 1, 2, and 3, given a value of p*, we can iteratively determine the optimal values of (l*, [alpha]*, [beta]*, [lambda]*) using the bisection search method or the Golden section method in the four single variable suboptimization
problems that are decoupled from the original problem in terms of l, [alpha], [beta], and [lambda] .
The more a cost-imposition calculus expands beyond suboptimization
of a specific contest, the more hardship differential becomes less relevant than which nation has the best overall strategy.
According to the dual theory, we can get the following equation for the rate suboptimization
problem from (16):
For Case 2, if the link qualities from CUs to the mth PU are assumed to be much better than those from BS to CUs, that [P.sub.C][[beta].sub.m,k] >> [P.sub.bs][[alpha].sub.m,k] and [P.sub.C][[beta].sub.m,k] >> N (k = 1, 2, ..., K), which implies that the noise amplification effect at CUs for the data transmission of the mth PU is negligible, we can derive a suboptimization
problem for (14) or 13a)-(13b) as
Hence, (19) transforms the suboptimization
problem about k as follows:
Let [[summation].sup.s.sub.r=1] [u.sub.r][y.sub.rj]/[[summation].sup.m.sub.i=1] [v.sub.i][x.sub.ij] = 1 for any "DEA efficient" DMU; then (6) is separated into p suboptimization
problems (j = [J.sub.1], ..., [J.sub.p]) in which p is the number of "DEA efficient" units and [J.sub.1], ..., [J.sub.p] are the "DEA efficient" DMUs.
Failure to integrate contracting with all of the three primary pillars will result in suboptimization
or outright contract support and/or mission failure (Yoder, 2010).
Perhaps the most evident is suboptimization
can be understood as failing to recognize the wholeness and connectedness of a system (Hutchins, 1996).
Another important advantage of LCA is that it includes all related processes, and studies an entire product system, hence, avoiding the suboptimization
that could result if only a single process were the focus of the study.
Simply doing the best for individual components amounts to suboptimization
and results in losses to everybody in the system.