An Efficient Random Algorithm for Box Constrained Weighted Maximin Dispersion Problem ()
ABSTRACT
The box-constrained weighted maximin dispersion
problem is to find a point in an n-dimensional box such that the minimum of the
weighted Euclidean distance from given m points is maximized. In this paper, we first reformulate the maximin dispersion problem as a non-convex quadratically constrained
quadratic programming (QCQP) problem. We adopt the successive convex approximation (SCA) algorithm to solve the
problem. Numerical results show that the proposed algorithm is efficient.
Share and Cite:
Huang, J. (2019) An Efficient Random Algorithm for Box Constrained Weighted Maximin Dispersion Problem.
Advances in Pure Mathematics,
9, 330-336. doi:
10.4236/apm.2019.94015.
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