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中文摘要：
本文提出了一个求不定二次规划问题全局最优解的新算法．首先，给出了三种计算下界的方法：线性逼近法、凸松弛法和拉格朗日松弛法；并且证明了拉格朗日对偶界与通过凸松弛得到的下界是相等的；然后建立了基于拉格朗日对偶界和矩形两分法的分枝定界算法，并给出了初步的数值试验结果．
英文摘要：
In this paper we propose a new algorithm for finding a global solution of indefinite quadratic programming problems. We first derive three lower bounding techniques： linear approximation, convex relaxation and Lagrangian relaxation. We prove that the Lagrangian dual bound is identical to the lower bound obtained by convex relaxation. A branch-and-bound algorithm based on the Lagrangian lower bounds and rectangular bisection is then presented with preliminary computational results.
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