### Abstract

Mathematical researchers have, over the past decade, developed an efficient class of linear programming solvers known as interior-point methods. Interior-point methods have theoretical and observed computational advantage over simplex methods at solving many large linear programming problems and are immune to degeneracy. Common nonlinear programming methods which work well for small and medium sized problems are unable to solve large-scale problems in a timely fashion. Used in an adaptive sequential linear programming strategy, interior-point methods can be a powerful engineering optimization tool. This work demonstrates the application of an adaptive sequential linear programming algorithm that uses an infeasible primal-dual path-following interior-point algorithm and fuzzy heuristics for the solution of large-scale engineering design optimization problems. Numerical examples demonstrate the superiority of interior-point methods compared to well-known simplex-based linear solver in solving large optimum design problems. Superior performance is shown in both computational time and algorithm ability to handle degenerate problems.

Original language | English (US) |
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Title of host publication | Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference |

Editors | Anon |

Publisher | AIAA |

Pages | 2175-2180 |

Number of pages | 6 |

Volume | 3 |

State | Published - 1998 |

Externally published | Yes |

Event | Proceedings of the 1998 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibit and AIAA/ASME/AHS Adaptive Structures Forum. Part 1 (of 4) - Long Beach, CA, USA Duration: Apr 20 1998 → Apr 23 1998 |

### Other

Other | Proceedings of the 1998 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibit and AIAA/ASME/AHS Adaptive Structures Forum. Part 1 (of 4) |
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City | Long Beach, CA, USA |

Period | 4/20/98 → 4/23/98 |

### Fingerprint

### ASJC Scopus subject areas

- Architecture

### Cite this

*Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference*(Vol. 3, pp. 2175-2180). AIAA.

**Sequential linear programming with interior-point methods for large-scale optimization.** / Mulkay, Eric L.; Rao, Singiresu S.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference.*vol. 3, AIAA, pp. 2175-2180, Proceedings of the 1998 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibit and AIAA/ASME/AHS Adaptive Structures Forum. Part 1 (of 4), Long Beach, CA, USA, 4/20/98.

}

TY - GEN

T1 - Sequential linear programming with interior-point methods for large-scale optimization

AU - Mulkay, Eric L.

AU - Rao, Singiresu S

PY - 1998

Y1 - 1998

N2 - Mathematical researchers have, over the past decade, developed an efficient class of linear programming solvers known as interior-point methods. Interior-point methods have theoretical and observed computational advantage over simplex methods at solving many large linear programming problems and are immune to degeneracy. Common nonlinear programming methods which work well for small and medium sized problems are unable to solve large-scale problems in a timely fashion. Used in an adaptive sequential linear programming strategy, interior-point methods can be a powerful engineering optimization tool. This work demonstrates the application of an adaptive sequential linear programming algorithm that uses an infeasible primal-dual path-following interior-point algorithm and fuzzy heuristics for the solution of large-scale engineering design optimization problems. Numerical examples demonstrate the superiority of interior-point methods compared to well-known simplex-based linear solver in solving large optimum design problems. Superior performance is shown in both computational time and algorithm ability to handle degenerate problems.

AB - Mathematical researchers have, over the past decade, developed an efficient class of linear programming solvers known as interior-point methods. Interior-point methods have theoretical and observed computational advantage over simplex methods at solving many large linear programming problems and are immune to degeneracy. Common nonlinear programming methods which work well for small and medium sized problems are unable to solve large-scale problems in a timely fashion. Used in an adaptive sequential linear programming strategy, interior-point methods can be a powerful engineering optimization tool. This work demonstrates the application of an adaptive sequential linear programming algorithm that uses an infeasible primal-dual path-following interior-point algorithm and fuzzy heuristics for the solution of large-scale engineering design optimization problems. Numerical examples demonstrate the superiority of interior-point methods compared to well-known simplex-based linear solver in solving large optimum design problems. Superior performance is shown in both computational time and algorithm ability to handle degenerate problems.

UR - http://www.scopus.com/inward/record.url?scp=0031699304&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031699304&partnerID=8YFLogxK

M3 - Conference contribution

VL - 3

SP - 2175

EP - 2180

BT - Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

A2 - Anon, null

PB - AIAA

ER -