کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
404277 677408 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A deterministic annealing algorithm for approximating a solution of the linearly constrained nonconvex quadratic minimization problem
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A deterministic annealing algorithm for approximating a solution of the linearly constrained nonconvex quadratic minimization problem
چکیده انگلیسی

A deterministic annealing algorithm is proposed for approximating a solution of the linearly constrained nonconvex quadratic minimization problem. The algorithm is derived from applications of a Hopfield-type barrier function in dealing with box constraints and Lagrange multipliers in handling linear equality constraints, and attempts to obtain a solution of good quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the algorithm searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that the box constraints are always satisfied automatically if the step length is a number between zero and one. At each iteration, the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the algorithm converges to a stationary point of the barrier problem. Preliminary numerical results show that the algorithm seems effective and efficient.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 39, March 2013, Pages 1–11
نویسندگان
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