计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (17): 49-52.

• 理论研究 • 上一篇    下一篇

非凸二次规划全局极小问题的新型分枝定界算法

杜廷松1,费浦生2,蹇继贵1   

  1. 1. 三峡大学 非线性与复杂系统研究所,湖北 宜昌 443002
    2. 武汉大学 数学与计算科学学院,武汉 430072
  • 收稿日期:2007-09-14 修回日期:2007-12-27 出版日期:2008-06-11 发布日期:2008-06-11
  • 通讯作者: 杜廷松

New branch and bound algorithm for nonconvex quadratic programming global minimization

DU Ting-song1,FEI Pu-sheng2,JIAN Ji-gui1   

  1. 1. Institute of Nonlinear and Complex Systems,China Three Gorges University,Yichang,Hubei 443002,China
    2. College of Mathematics and Computer Science,Wuhan University,Wuhan 430072,China
  • Received:2007-09-14 Revised:2007-12-27 Online:2008-06-11 Published:2008-06-11
  • Contact: DU Ting-song

摘要: 针对求解多面集上二次函数的全局近似最优解问题,利用逐步缩小对偶间隙的处理办法,提出了一个新型分枝定界算法。新算法的主要改进之处是利用了Lagrange 对偶性获取下界。最后,用构造和随机产生的问题实例,对提出的新算法和传统的分枝定界算法做了初步的数值比较实验。计算实验表明算法对求解中大规模非凸二次规划问题的有效性。

Abstract: In this paper,by using a technique for reducing the duality gap,a new branch and bound algorithm is developed for quadratic programming global minimization.The major improvement of the new algorithm is that the algorithm uses Lagrangian duality to obtain lower bounds.In the last,two different algorithms(namely,the proposed algorithm,the traditional branch and bound algorithm)have been implemented for same construction problems and random instances.Computation results indicate that the proposed algorithm can solve large-scale nonconvex quadratic problems.