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The use of lower bounds in minimization by the interior-point method

 Аннотация

    An interior-point method for the convex minimization problem is proposed. On each iteration, an auxiliary relaxed problem of computing the lower bound of the optimum is solved. The rate of decrease of the difference between the current value of the objective function and the lower bound is investigated. The auxiliary relaxed problem is solved in the linear case.

 Ключевые слова

    interior-point method, convex programming, lower bound of the optimum
 


Последние изменения: 27.02.2001


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