A Global Optimization Algorithm for Sum of Quadratic Ratios Problem with Coefficients

摘要：

　　In this paper a global optimization algorithm for solving sum of quadratic ratios problem with coefficients and nonconvex quadratic function constraints (NSP) is proposed.First,the problem NSP is converted into an equivalent sum of linear ratios problem with nonconvex quadratic constraints (LSP).Using linearization technique,the linearization relaxation of LSP is obtained.The whole problem is then solvable using the branch and bound method.In the algorithm,lower bounds are derived by solving a sequence of linear lower bounding functions for the objective function and the constraint functions of the problem NSP over the feasible region.The proposed algorithm is convergent to the global minimum through the successive refinement of the solutions of a series of linear programming problems.The numerical examples demonstrate that the proposed algorithm can easily be applied to solve problem NSP.

关键词： Quadratic Ratios Problem quadratic constraints problem linearization relaxation branch and bound global convergence

作者: Ji Ying Li Yijun

作者单位: School of Management, Academy of Fundamental and Interdisciplinary Science Harbin Institute of Techn School of Management Harbin Institute of Technology Harbin,China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer Application and System Modeling(2012第二届计算机应用与系统建模国际会议)(ICCASM-2012)

会议地点: 沈阳

会议语种:英文

页码: 1305-1307

在线出版日期: 2012-07-27（万方平台首次上网日期，不代表论文的发表时间）