The book had done the hard work, converting problem-solving into mindless instruction-following: identify the problem type, apply the algorithm.
Recently, similar problems are studied in ordered Banach spaces, e.g., in [1 4], by converting problems into systems of integral equations, integrals in these systems being Bochner-Lebesgue or Henstock-Kurzweil integrals.
we convert problem (1.6) into (2.6).
Let us first construct a transformation to convert Problem 1 to an equivalent integer programming problem.
We first convert problem (MIQQP) into an equivalent generalized bilinear programming problem with integer variables (EIQQP).
By means of the transformation (2.5), we can convert problem (4.1) into (4.2). (4.3).
We can convert problem (11) to min_{boldsymbol{phi}} J boldsymbol{phi}), (24).
These conventions will prove to be sufficient to convert Problem 3 into another formulation of Problem 2, now as a minimization problem.
To convert the non-convex quadratic distance constraints into convex constraints, we introduce a relaxation to remove the quadratic terms in the formulation to convert problem (13) into a standard SDP problem as Eq. (14) (see Appendix).
Moreover, for applications in which computational complexity is a major issue, a similar algorithm as Algorithm 2 can be devised resorting to the alternating maximization technique, in order to convert problem (17) into a sequence of scalar problems.
