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Study of the sequential constraint-handling technique for evolutionary optimization with application to structural problems

Motte, Damien LU orcid ; Nordin, Axel LU and Bjärnemo, Robert LU (2011) 37th Design Automation Conference - DETC/DAC'11 5. p.521-531
Abstract
Engineering design problems are most frequently charac-terized by constraints that make them hard to solve and time-consuming. When evolutionary algorithms are used to solve these problems, constraints are often handled with the generic weighted sum method or with techniques specific to the prob-lem at hand. Most commonly, all constraints are evaluated at each generation, and it is also necessary to fine-tune different parameters in order to receive good results, which requires in-depth knowledge of the algorithm. The sequential constraint-handling techniques seem to be a promising alternative, be-cause they do not require all constraints to be evaluated at each iteration and they are easy to implement. They neverthe-less require the user... (More)
Engineering design problems are most frequently charac-terized by constraints that make them hard to solve and time-consuming. When evolutionary algorithms are used to solve these problems, constraints are often handled with the generic weighted sum method or with techniques specific to the prob-lem at hand. Most commonly, all constraints are evaluated at each generation, and it is also necessary to fine-tune different parameters in order to receive good results, which requires in-depth knowledge of the algorithm. The sequential constraint-handling techniques seem to be a promising alternative, be-cause they do not require all constraints to be evaluated at each iteration and they are easy to implement. They neverthe-less require the user to determine the ordering in which those constraints shall be evaluated. Therefore two heuristics that allow finding a satisfying constraint sequence have been developed. Two sequential constraint-handling techniques using the heuristics have been tested against the weighted sum technique with the ten-bar structure benchmark. They both performed better than the weighted sum technique and can therefore be easy to implement, and powerful alternatives for solving engineering design problems. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
constraint-handling techniques, evolutionary computing, genetic algorithms, structural optimisation, Renaissance 2.0, machine design, maskinkonstruktion
host publication
Proceedings of the 37th Design Automation Conference - DETC/DAC'11
volume
5
article number
DETC2011-47057
pages
11 pages
publisher
American Society Of Mechanical Engineers (ASME)
conference name
37th Design Automation Conference - DETC/DAC'11
conference dates
2011-08-29 - 2011-08-31
external identifiers
  • wos:000324076700049
  • scopus:84863592083
ISBN
978-0-7918-5482-2
DOI
10.1115/DETC2011-47057
language
English
LU publication?
yes
additional info
The two first authors contributed equally
id
b140089a-c3e6-4c9a-b113-38160c871895 (old id 1788917)
date added to LUP
2016-04-04 11:32:32
date last changed
2023-01-06 00:03:32
@inproceedings{b140089a-c3e6-4c9a-b113-38160c871895,
  abstract     = {{Engineering design problems are most frequently charac-terized by constraints that make them hard to solve and time-consuming. When evolutionary algorithms are used to solve these problems, constraints are often handled with the generic weighted sum method or with techniques specific to the prob-lem at hand. Most commonly, all constraints are evaluated at each generation, and it is also necessary to fine-tune different parameters in order to receive good results, which requires in-depth knowledge of the algorithm. The sequential constraint-handling techniques seem to be a promising alternative, be-cause they do not require all constraints to be evaluated at each iteration and they are easy to implement. They neverthe-less require the user to determine the ordering in which those constraints shall be evaluated. Therefore two heuristics that allow finding a satisfying constraint sequence have been developed. Two sequential constraint-handling techniques using the heuristics have been tested against the weighted sum technique with the ten-bar structure benchmark. They both performed better than the weighted sum technique and can therefore be easy to implement, and powerful alternatives for solving engineering design problems.}},
  author       = {{Motte, Damien and Nordin, Axel and Bjärnemo, Robert}},
  booktitle    = {{Proceedings of the 37th Design Automation Conference - DETC/DAC'11}},
  isbn         = {{978-0-7918-5482-2}},
  keywords     = {{constraint-handling techniques; evolutionary computing; genetic algorithms; structural optimisation; Renaissance 2.0; machine design; maskinkonstruktion}},
  language     = {{eng}},
  pages        = {{521--531}},
  publisher    = {{American Society Of Mechanical Engineers (ASME)}},
  title        = {{Study of the sequential constraint-handling technique for evolutionary optimization with application to structural problems}},
  url          = {{https://lup.lub.lu.se/search/files/5797863/3052047.pdf}},
  doi          = {{10.1115/DETC2011-47057}},
  volume       = {{5}},
  year         = {{2011}},
}