期刊
JOURNAL OF GLOBAL OPTIMIZATION
卷 22, 期 1-4, 页码 155-174出版社
KLUWER ACADEMIC PUBL
DOI: 10.1023/A:1013807129844
关键词
global optimization; nonconvex optimization; fractional programming; sum of linear ratios; branch-and-bound algorithm
In this paper, we develop a branch-and-bound algorithm for maximizing a sum of p (greater than or equal to2) linear ratios on a polytope. The problem is embedded into a 2p-dimensional space, in which a concave polyhedral function overestimating the optimal value is constructed for the bounding operation. The branching operation is carried out in a p-dimensional space, in a way similar to the usual rectangular branch-and-bound method. We discuss the convergence properties and report some computational results.
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