An Efficient Random Algorithm for Box Constrained Weighted Maximin Dispersion Problem - Advances in Pure Mathematics

APM > Vol.9 No.4, April 2019

An Efficient Random Algorithm for Box Constrained Weighted Maximin Dispersion Problem ()

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Download as PDF (Size: 370KB) PP. 330-336

DOI: 10.4236/apm.2019.94015 575 Downloads 1,074 Views

Author(s)

Jinjin Huang

Affiliation(s)

Department of Mathematics, Shanghai University, Shanghai, China.

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.

KEYWORDS

Maximin Dispersion Problem, Successive Convex Approximation Algorithm, Quadratically Constrained Quadratic Programming (QCQP)

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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