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A Mathematical Programming Algorithm for Multidisciplinary Design Optimization

Authors: José Herskovits;

A Mathematical Programming Algorithm for Multidisciplinary Design Optimization

Abstract

Mathematical Programming provides general tools for Engineering Design Optimization. We present a numerical models for Multidisciplinary Design Optimization (MDO) represented by a Mathematical Programming problem and a new numerical algorithm to solve this problem. Our technique is based on the Feasible Arc Interior Point Algorithm for Nonlinear Constrained Optimization, FAIPA. Even if MDO is a very large optimization problem, our approach considerably reduces the computer efiort. Several tools for very large problems are also presented. The present approach is very strong and e‐cient for real industrial applications and can easily interact with existing simulation and optimization engineering codes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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