Year: 2004
Author: Honggang Xue, Chengxian Xu, Fengmin Xu
Journal of Computational Mathematics, Vol. 22 (2004), Iss. 6 : pp. 895–904
Abstract
In this paper, we propose a new branch and bound algorithm for the solution of large scale separable concave programming problems. The largest distance bisection (LDB) technique is proposed to divide rectangle into sub-rectangles when one problem is branched into two subproblems. It is proved that the LDB method is a normal rectangle subdivision (NRS). Numerical tests on problems with dimensions from 100 to 10000 show that the proposed branch and bound algorithm is efficient for solving large scale separable concave programming problems, and convergence rate is faster than $w$-subdivision method.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2004-JCM-10293
Journal of Computational Mathematics, Vol. 22 (2004), Iss. 6 : pp. 895–904
Published online: 2004-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10
Keywords: Branch and bound algorithm Separable programming Largest distance bisection Normal rectangle subdivision $w$-subdivision.