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A PRIMAL-DUAL INTERIOR-POINT METHOD CAPABLE OF RAPIDLY DETECTING INFEASIBILITY FOR NONLINEAR PROGRAMS

机译:一种能够快速检测非线性程序的不可行性的原始 - 双内点方法

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摘要

With the help of a logarithmic barrier augmented Lagrangian function, we can obtain closed-form solutions of slack variables of logarithmic-barrier problems of nonlinear programs. As a result, a two-parameter primal-dual nonlinear system is proposed, which corresponds to the Karush-Kuhn-Tucker point and the infeasible stationary point of nonlinear programs, respectively, as one of two parameters vanishes. Based on this distinctive system, we present a primal-dual interior-point method capable of rapidly detecting infeasibility of nonlinear programs. The method generates interior-point iterates without truncation of the step. It is proved that our method converges to a Karush-Kuhn-Tucker point of the original problem as the barrier parameter tends to zero. Otherwise, the scaling parameter tends to zero, and the method converges to either an infeasible stationary point or a singular stationary point of the original problem. Moreover, our method has the capability to rapidly detect the infeasibility of the problem. Under suitable conditions, the method can be superlinearly or quadratically convergent to the Karush-Kuhn-Tucker point if the original problem is feasible, and it can be superlinearly or quadratically convergent to the infeasible stationary point when the problem is infeasible. Preliminary numerical results show that the method is efficient in solving some simple but hard problems, where the superlinear convergence to an infeasible stationary point is demonstrated when we solve two infeasible problems in the literature.
机译:在对数屏障增强拉格朗日功能的帮助下,我们可以获得非线性程序对数屏障问题的封闭变量的封闭式解决方案。结果,提出了一种双参数原始 - 双非线性系统,其对应于karush-kuhn-tucker点和非线性程序的不可行的静止点,因为两个参数之一消失。基于这种独特的系统,我们提出了一种能够快速检测非线性程序的不可行的原始 - 双内点方法。该方法在不截断步骤的情况下生成内部点迭代。事实证明,随着屏障参数趋于为零,我们的方法会聚到原始问题的karush-kuhn-tucker点。否则,缩放参数趋于为零,并且该方法会聚到原始问题的不可行的静止点或单个静止点。此外,我们的方法具有快速检测问题的不可行性。在合适的条件下,如果原始问题是可行的,则该方法可以超级或二次地会聚到karush-kuhn-tucker点,并且当问题是不可行的时,它可以超级或二次地会聚到可行的静止点。初步数值结果表明,该方法在解决一些简单但艰难的问题方面是有效的,当我们在文献中解决两个不可行的问题时,证明了对不可行的固定点的超连线收敛。

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