| Descending Dimension Algorithm of Nolinear Programming Problem with Linear Inequality Constraints |
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| 引用本文： | YANG Yi,ZHANG Shou-gui. Descending Dimension Algorithm of Nolinear Programming Problem with Linear Inequality Constraints[J]. 保鲜与加工, 2007, 0(10): 42-45 |
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| 作者姓名： | YANG Yi ZHANG Shou-gui |
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| 作者单位： | 1. Department of Computer Science and Technology Chongqing University, Chongqing 400030, China; 2. College of Mathematics and Computer Science, Chongqing Normal University Chongqing 400047, China |
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| 摘 要： | The general nonlinear programming with linear constraints was investigated. In the algorithm, the method of contributing set was used. Comparing with the general contributing set method, the descending dimension method was used to solve the sub-problem with equality constraints in iterative procedure and the problem with inequality constraints. The algorithm is effective by the numerical test. Finally, it was proved that the iteration points are descending, when the objective functions are convex.
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| 关 键 词： | nonlinear programming problems linear inequality constraints descending dimension algorithm |
| 修稿时间： | 2007-05-12 |
Descending Dimension Algorithm of Nolinear Programming Problem with Linear Inequality Constraints |
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| YANG Yi,ZHANG Shou-gui. Descending Dimension Algorithm of Nolinear Programming Problem with Linear Inequality Constraints[J]. Storage & Process, 2007, 0(10): 42-45 |
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| Authors: | YANG Yi ZHANG Shou-gui |
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| Affiliation: | 1. Department of Computer Science and Technology Chongqing University, Chongqing 400030, China; 2. College of Mathematics and Computer Science, Chongqing Normal University Chongqing 400047, China |
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| Abstract: | The general nonlinear programming with linear constraints was investigated. In the algorithm, the method of contributing set was used. Comparing with the general contributing set method, the descending dimension method was used to solve the sub-problem with equality constraints in iterative procedure and the problem with inequality constraints. The algorithm is effective by the numerical test. Finally, it was proved that the iteration points are descending, when the objective functions are convex. |
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| Keywords: | nonlinear programming problems linear inequality constraints descending dimension algorithm |
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