Cross-Hill: A heuristic method for global optimization

被引:1
|
作者
Wu, Tingting [1 ]
Han, Deren [2 ]
Xu, Yi [3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Sch Sci, Nanjing 210023, Jiangsu, Peoples R China
[2] Nanjing Normal Univ, Sch Math Sci, Key Lab NSLSCS Jiangsu Prov, Nanjing 210023, Jiangsu, Peoples R China
[3] Southeast Univ, Dept Appl Math, Nanjing, Jiangsu, Peoples R China
关键词
Cross-Hill; Global Optimization; Tensor; Polynomial optimization; Local method; Gradient descent method; APPROXIMATION; EIGENVALUES; RANK-1;
D O I
10.1016/j.amc.2015.06.013
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The heuristic Cross Hill method proposed by Qi et al. (2009) [14] was recently extended from finding the Z-eigenvalues of tensors to quantum separation problem by Han and Qi (2013) [5]. In this paper, we show that it can be extended to solve general global optimization problems. The heuristic Cross Hill method is a combination of a local optimization method and a global optimization method with lower dimension. At each iteration, it first uses the local optimization method to find a local solution. Then, using this point and an arbitrary orthogonal vector, it solves a two-dimensional optimization problem to find a better solution than that the local approach was able to find. Preliminary experimental results are very encouraging. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:959 / 967
页数:9
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