Formulating and Solving Nonlinear Programs as Mixed Complementarity Problems
Formulating and Solving Nonlinear Programs as Mixed Complementarity Problems
复制标题
将非线性规划制定为混合互补问题并求解
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
K. Sinapiromsaran
中科院分区：
文献类型：
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作者：
M. Ferris;K. Sinapiromsaran
我们考虑了一种原始对偶方法来解决AMPL建模语言中的非线性规划问题，通过混合互补公式。该建模语言利用自动微分提供非线性问题拉格朗日函数的一阶和二阶导数信息。PATH求解器根据这些导数信息自动生成一阶条件的解。此外，该环节还将目标函数引入PATH求解器的新优点函数中，提高了互补算法求解非线性规划最优解的能力。我们在文献中的各种测试套件上测试了新的求解器，并与其他可用的非线性规划求解器进行了比较。
We consider a primal-dual approach to solve nonlinear programming problems within the AMPL modeling language, via a mixed complementarity formulation. The modeling language supplies the first order and second order derivative information of the Lagrangian function of the nonlinear problem using automatic differentiation. The PATH solver finds the solution of the first order conditions which are generated automatically from this derivative information. In addition, the link incorporates the objective function into a new merit function for the PATH solver to improve the capability of the complementarity algorithm for finding optimal solutions of the nonlinear program. We test the new solver on various test suites from the literature and compare with other available nonlinear programming solvers.