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A new branch and bound algorithm for minimax ratios problems : Open Mathematics

机译:极大极小比率问题的一种新的分支定界算法:开放数学

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摘要

This study presents an efficient branch and bound algorithm for globally solving the minimax fractional programming problem (MFP). By introducing an auxiliary variable, an equivalent problem is firstly constructed and the convex relaxation programming problem is then established by utilizing convexity and concavity of functions in the problem. Other than usual branch and bound algorithm, an adapted partition skill and a practical reduction technique performed only in an unidimensional interval are incorporated into the algorithm scheme to significantly improve the computational performance. The global convergence is proved. Finally, some comparative experiments and a randomized numerical test are carried out to demonstrate the efficiency and robustness of the proposed algorithm.
机译:这项研究提出了一种有效的分支定界算法,用于全局解决极小极大分数编程问题(MFP)。通过引入辅助变量,首先构造一个等价问题,然后利用该问题中函数的凸性和凹性来建立凸松弛规划问题。除了通常的分支定界算法之外,仅在一维间隔中执行的自适应分区技术和实用归约技术被合并到算法方案中,以显着提高计算性能。证明了全局收敛。最后,通过一些比较实验和随机数值测试证明了该算法的有效性和鲁棒性。

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