Study of the sequential constraint-handling technique for evolutionary optimization with application to structural problems
(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:
https://lup.lub.lu.se/record/1788917
- author
- Motte, Damien LU ; Nordin, Axel LU and Bjärnemo, Robert LU
- organization
- publishing date
- 2011
- 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}}, }