Parallel direct search in structural optimization

João Mário Burguete Botelho Cardoso; Pedro Coelho; Ana Luísa da Graça Batista Custódio

doi:10.4203/ccp.95.48

Parallel direct search in structural optimization

João Mário Burguete Botelho Cardoso, Pedro Coelho, Ana Luísa da Graça Batista Custódio

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

Abstract

Since its early heuristic development, Direct Search Methods (DSM) have proved to be robust and reliable, both from theoretical and practical perspectives. Some of these algorithms are now able to solve noisy, nonsmooth or nonconvex problems and its algorithmic structure favours parallelization, drawing the attention of the structural optimization community as a promising alternative to the use of Meta-Heuristics.

In the present work, the performance of DSM is compared to Genetic Algorithms, when solving hard or expensive structural optimization problems. Parallel implementations are considered when large computational times are involved in function evaluation.

Original language	Unknown
Title of host publication	PARENG 2011
Pages	Paper 48
DOIs	https://doi.org/10.4203/ccp.95.48
Publication status	Published - 1 Jan 2011
Event	The Second International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering - Duration: 1 Jan 2011 → …

Conference

Conference	The Second International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering
Period	1/01/11 → …

Access to Document

10.4203/ccp.95.48

Cite this

@inproceedings{cf633ec862894dcbae50520caf200129,

title = "Parallel direct search in structural optimization",

abstract = "Since its early heuristic development, Direct Search Methods (DSM) have proved to be robust and reliable, both from theoretical and practical perspectives. Some of these algorithms are now able to solve noisy, nonsmooth or nonconvex problems and its algorithmic structure favours parallelization, drawing the attention of the structural optimization community as a promising alternative to the use of Meta-Heuristics.In the present work, the performance of DSM is compared to Genetic Algorithms, when solving hard or expensive structural optimization problems. Parallel implementations are considered when large computational times are involved in function evaluation.",

keywords = "Structural Optimization, Mesh Adaptive Direct Search, Parallel Computing, Direct Search Methods, Genetic Algorithms, Derivative-Free Optimization, Pattern Search Methods",

author = "Cardoso, {Jo{\~a}o M{\'a}rio Burguete Botelho} and Pedro Coelho and Cust{\'o}dio, {Ana Lu{\'i}sa da Gra{\c c}a Batista}",

year = "2011",

month = jan,

day = "1",

doi = "10.4203/ccp.95.48",

language = "Unknown",

isbn = "978-1-905088-43-0",

pages = "Paper 48",

booktitle = "PARENG 2011",

note = "The Second International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering ; Conference date: 01-01-2011",

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T1 - Parallel direct search in structural optimization

AU - Cardoso, João Mário Burguete Botelho

AU - Coelho, Pedro

AU - Custódio, Ana Luísa da Graça Batista

PY - 2011/1/1

Y1 - 2011/1/1

N2 - Since its early heuristic development, Direct Search Methods (DSM) have proved to be robust and reliable, both from theoretical and practical perspectives. Some of these algorithms are now able to solve noisy, nonsmooth or nonconvex problems and its algorithmic structure favours parallelization, drawing the attention of the structural optimization community as a promising alternative to the use of Meta-Heuristics.In the present work, the performance of DSM is compared to Genetic Algorithms, when solving hard or expensive structural optimization problems. Parallel implementations are considered when large computational times are involved in function evaluation.

AB - Since its early heuristic development, Direct Search Methods (DSM) have proved to be robust and reliable, both from theoretical and practical perspectives. Some of these algorithms are now able to solve noisy, nonsmooth or nonconvex problems and its algorithmic structure favours parallelization, drawing the attention of the structural optimization community as a promising alternative to the use of Meta-Heuristics.In the present work, the performance of DSM is compared to Genetic Algorithms, when solving hard or expensive structural optimization problems. Parallel implementations are considered when large computational times are involved in function evaluation.

KW - Structural Optimization

KW - Mesh Adaptive Direct Search

KW - Parallel Computing

KW - Direct Search Methods

KW - Genetic Algorithms

KW - Derivative-Free Optimization

KW - Pattern Search Methods

U2 - 10.4203/ccp.95.48

DO - 10.4203/ccp.95.48

M3 - Conference contribution

SN - 978-1-905088-43-0

SP - Paper 48

BT - PARENG 2011

T2 - The Second International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering

Y2 - 1 January 2011

ER -