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作 者:Bo Zhang Yuelin Gao Xia Liu Xiaoli Huang
机构地区:[1]School of Civil and Hydraulic Engineering,School of Mathematics and Statistics,Ningxia University,Yinchuan 750021,China [2]School of Mathematics and Information Science,North Minzu University,Yinchuan 750021,China [3]Ningxia Province Key Laboratory of Intelligent Information and Data Processing,Yinchuan 750021,China [4]School of Mathematics and Statistics,Ningxia University,Yinchuan 750021,China
出 处:《Journal of Computational Mathematics》2024年第3期784-813,共30页计算数学(英文)
基 金:supported by the National Natural Science Foundation of China(Grant 11961001);the construction project of first-class subjects in Ningxia Higher Education(Grant NXYLXK2017B09);by the major proprietary funded project of North Minzu University(Grant ZDZX201901).
摘 要:The mixed-integer quadratically constrained quadratic fractional programming(MIQCQFP)problem often appears in various fields such as engineering practice,management science and network communication.However,most of the solutions to such problems are often designed for their unique circumstances.This paper puts forward a new global optimization algorithm for solving the problem MIQCQFP.We first convert the MIQCQFP into an equivalent generalized bilinear fractional programming(EIGBFP)problem with integer variables.Secondly,we linearly underestimate and linearly overestimate the quadratic functions in the numerator and the denominator respectively,and then give a linear fractional relaxation technique for EIGBFP on the basis of non-negative numerator.After that,combining rectangular adjustment-segmentation technique and midpointsampling strategy with the branch-and-bound procedure,an efficient algorithm for solving MIQCQFP globally is proposed.Finally,a series of test problems are given to illustrate the effectiveness,feasibility and other performance of this algorithm.
关 键 词:Global optimization Branch and bound Quadratic fractional programming Mixed integer programming
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