申培萍 王亞飛 吳殿曉



摘 要:研究了一類Minimax分式規劃問題(MFP).首先通過引進變量,將問題(MFP)等價轉化為問題(EP1),其次,再將問題(EP1)中的約束函數整理成正項式的形式,然后,利用特殊不等式的性質將問題(EP1)轉化為易于求解的幾何規劃問題(GP),通過求解一系列(GP) 問題獲得原問題的最優解,最后,給出求解問題(MFP)的迭代算法以及算法的收斂性分析,數值結果表明了算法的有效性.
關鍵詞:Minimax分式規劃;幾何規劃;迭代算法
中圖分類號:O221.2文獻標志碼:A
從表1中的數值結果可知,本文提出的算法與文獻[9-10]中的其他方法相比,可以在較少的次數內得到問題的解,并且獲得的最優值優于文獻[9-10]獲得的最優值.另外,本文提出的算法的迭代次數以及運行時間均少于文獻[9-10]中的數據.
5 結 論
本文考慮一類Minimax分式規劃問題并提出相應的算法,首先,通過引入輔助變量將其轉化為等價問題,然后根據等價問題的自身特點,將其轉化為形式更簡單的(Q)問題,最后,再利用不等式的性質,將(Q)問題轉化為一系列易于求解的幾何規劃問題,數值結果表明了算法的可行性和有效性.另外,該模型也可以應用于特殊模型的求解.
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Iterative a geometric programming method for solving a class of minimax fractional optimization problems
Shen Peiping, Wang Yafei, Wu Dianxiao
(School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
Abstract: This paper studies a class of Minimax fractional programming problems. Firstly, by introducing variables, the problem (MFP) is equivalently converted to problem (EP1). Secondly, the constraint function in the problem (EP1) is organized into a positive term. Then, by using the properties of special inequalities, problem (EP1) is transformed into an easy-to-solve geometric programming problem (GP), and the optimal solution of the original problem is obtained by solving a series of (GP) problems.? Finally, the iterative algorithm for solving problem (MFP) and the convergence analysis of the algorithm are given, and the numerical results show that the algorithm is feasible and effective.
Keywords: Minimax fractional programming; geometric programming; iterative algorithm
[責任編校 陳留院 趙曉華]