A branch-and-bound algorithm for discrete multi-factor by Niu Shu-fen, Wang Guo-xin, Sun Xiao-ling

By Niu Shu-fen, Wang Guo-xin, Sun Xiao-ling

During this paper, a brand new branch-and-bound set of rules in response to the Lagrangian twin leisure and non-stop rest is proposed for discrete multi-factor portfolio choice version with roundlot limit in monetary optimization. This discrete portfolio version is of integer quadratic programming difficulties. The separable constitution of the version is investigated through the use of Lagrangian leisure and twin seek. Computational effects convey that the set of rules is able to fixing real-world portfolio issues of information from US inventory industry and randomly generated try out issues of as much as one hundred twenty securities.

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