期刊
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
卷 16, 期 2, 页码 127-138出版社
SPRINGER
DOI: 10.1007/s10100-007-0051-x
关键词
global optimization; branch and bound; branch and cut; outer approximation; mixed-integer nonlinear programming
We present a Branch and Cut algorithm of the software package LaGO to solve nonconvex mixed-integer nonlinear programs (MINLPs). A linear outer approximation is constructed from a convex relaxation of the problem. Since we do not require an algebraic representation of the problem, reformulation techniques for the construction of the convex relaxation cannot be applied, and we are restricted to sampling techniques in case of nonquadratic nonconvex functions. The linear relaxation is further improved by mixed-integer-rounding cuts. Also box reduction techniques are applied to improve efficiency. Numerical results on medium size test problems are presented to show the efficiency of the method.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据