线性规划的有限下降理论,分段线性凸最小化,线性互补问题

Daniel Solow, P. Sengupta
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引用次数: 12

摘要

提出了一种同时求解线性规划、分段线性凸最小化和线性互补问题的下降算法。给出了在有限次迭代中利用问题的几何性质找到解的条件。开发了一种计算机算法,并用该方法和Lemke算法解决了测试问题。目前的结果表明,访问的单元格数量减少了,但解决问题所需的枢轴总数增加了。
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A finite descent theory for linear programming, piecewise linear convex minimization, and the linear complementarity problem
A descent algorithm simultaneously capable of solving linear programming, piecewise linear convex minimization, and the linear complementarity problem is developed. Conditions are given under which a solution can be found in a finite number of iterations using the geometry of the problem. A computer algorithm is developed and test problems are solved by both this method and Lemke's algorithm. Current results indicate a decrease in the number of cells visited but an increase in the total number of pivots needed to solve the problem.
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