Article ID: | iaor200911689 |
Country: | United States |
Volume: | 41 |
Issue: | 3 |
Start Page Number: | 349 |
End Page Number: | 362 |
Publication Date: | Dec 2008 |
Journal: | Computational Optimization and Applications |
Authors: | Pan Shaohua, Tan Tao, Jiang Yuxi |
In this paper, we propose a new continuous approach for the unconstrained binary quadratic programming (BQP) problems based on the Fischer–Burmeister NCP function. Unlike existing relaxation methods, the approach reformulates a BQP problem as an equivalent continuous optimization problem, and then seeks its global minimizer via a global continuation algorithm which is developed by a sequence of unconstrained minimization for a global smoothing function. This smoothing function is shown to be strictly convex in the whole domain or in a subset of its domain if the involved barrier or penalty parameter is set to be sufficiently large, and consequently a global optimal solution can be expected. Numerical results are reported.