NEW BRANCH AND BOUND METHOD OVER A BOXED SET OF $\mathbb{R}^{n}$

B. Gasmi, R. Benacer
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Abstract

We present in this paper the new Branch and Bound method with new quadratic approach over a boxed set (a rectangle) of $\mathbb{R}^{n}$. We construct an approximate convex quadratics functions of the objective function to fined a lower bound of the global optimal value of the original non convex quadratic problem (NQP) over each subset of this boxed set. We applied a partition and technical reducing on the domain of (NQP) to accelerate the convergence of the proposed algorithm. Finally,we study the convergence of the proposed algorithm and we give a simple comparison between this method and another methods wish have the same principle.
在$\mathbb{R}^{n}$的盒子集合上新的分支和边界方法
本文在$\mathbb{R}^{n}$的框集(矩形)上给出了新的二次逼近分支定界法。我们构造了目标函数的一个近似凸二次函数,以确定原始非凸二次问题(NQP)在该盒集的每个子集上的全局最优值的下界。我们在(NQP)域上进行了划分和技术约简,加快了算法的收敛速度。最后,我们研究了该算法的收敛性,并将该方法与具有相同原理的其他方法进行了简单的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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