An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming
An interior point algorithm is proposed for linearly constrained convex programming following a parameterized central path, which is a generalization of the central path and requires weaker convergence conditions. The convergence and polynomial-time complexity of the proposed algorithm are proved un...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | English |
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SPRINGER/PLENUM PUBLISHERS
2022
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| Subjects: | |
| Online Access: | http://purl.org/au-research/grants/arc/DP160102918 http://hdl.handle.net/20.500.11937/91422 |
| _version_ | 1848765516244582400 |
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| author | Hou, L. Qian, X. Liao, L.Z. Sun, Jie |
| author_facet | Hou, L. Qian, X. Liao, L.Z. Sun, Jie |
| author_sort | Hou, L. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | An interior point algorithm is proposed for linearly constrained convex programming following a parameterized central path, which is a generalization of the central path and requires weaker convergence conditions. The convergence and polynomial-time complexity of the proposed algorithm are proved under the assumption that the Hessian of the objective function is locally Lipschitz continuous. In addition, an initialization strategy is proposed and some numerical results are provided to show the efficiency and attractiveness of the proposed algorithm. |
| first_indexed | 2025-11-14T11:36:29Z |
| format | Journal Article |
| id | curtin-20.500.11937-91422 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:36:29Z |
| publishDate | 2022 |
| publisher | SPRINGER/PLENUM PUBLISHERS |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-914222023-05-04T06:21:25Z An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming Hou, L. Qian, X. Liao, L.Z. Sun, Jie Science & Technology Physical Sciences Mathematics, Applied Mathematics Interior point method Path following Polynomial-time complexity Convex programming POTENTIAL REDUCTION ALGORITHM SCALING CONTINUOUS TRAJECTORIES PREDICTOR-CORRECTOR ALGORITHM CONTINUATION-SMOOTHING METHOD POLYNOMIAL-TIME ALGORITHM PRIMAL-DUAL ALGORITHMS LIMITING BEHAVIOR CONVERGENCE COMPLEXITY An interior point algorithm is proposed for linearly constrained convex programming following a parameterized central path, which is a generalization of the central path and requires weaker convergence conditions. The convergence and polynomial-time complexity of the proposed algorithm are proved under the assumption that the Hessian of the objective function is locally Lipschitz continuous. In addition, an initialization strategy is proposed and some numerical results are provided to show the efficiency and attractiveness of the proposed algorithm. 2022 Journal Article http://hdl.handle.net/20.500.11937/91422 10.1007/s10915-022-01765-3 English http://purl.org/au-research/grants/arc/DP160102918 SPRINGER/PLENUM PUBLISHERS restricted |
| spellingShingle | Science & Technology Physical Sciences Mathematics, Applied Mathematics Interior point method Path following Polynomial-time complexity Convex programming POTENTIAL REDUCTION ALGORITHM SCALING CONTINUOUS TRAJECTORIES PREDICTOR-CORRECTOR ALGORITHM CONTINUATION-SMOOTHING METHOD POLYNOMIAL-TIME ALGORITHM PRIMAL-DUAL ALGORITHMS LIMITING BEHAVIOR CONVERGENCE COMPLEXITY Hou, L. Qian, X. Liao, L.Z. Sun, Jie An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming |
| title | An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming |
| title_full | An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming |
| title_fullStr | An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming |
| title_full_unstemmed | An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming |
| title_short | An Interior Point Parameterized Central Path Following Algorithm for Linearly Constrained Convex Programming |
| title_sort | interior point parameterized central path following algorithm for linearly constrained convex programming |
| topic | Science & Technology Physical Sciences Mathematics, Applied Mathematics Interior point method Path following Polynomial-time complexity Convex programming POTENTIAL REDUCTION ALGORITHM SCALING CONTINUOUS TRAJECTORIES PREDICTOR-CORRECTOR ALGORITHM CONTINUATION-SMOOTHING METHOD POLYNOMIAL-TIME ALGORITHM PRIMAL-DUAL ALGORITHMS LIMITING BEHAVIOR CONVERGENCE COMPLEXITY |
| url | http://purl.org/au-research/grants/arc/DP160102918 http://hdl.handle.net/20.500.11937/91422 |