Abstract
BioSim is a simulation tool which captures many basic life support functions in an integrated simulation. Conventional analyses can not efficiently consider all possible life support system configurations. Heuristic approaches are a possible alternative. In an effort to demonstrate efficacy, a validating experiment was designed to compare the configurational optima discovered by heuristic approaches and an analytical approach. Thus far, it is clear that a genetic algorithm finds reasonable optima, although an improved fitness function is required. Further, despite a tight analytical fit to data, optimization produces disparate results which will require further validation.
| Original language | English (US) |
|---|---|
| Journal | SAE Technical Papers |
| DOIs | |
| State | Published - Jan 1 2007 |
| Event | 37th International Conference on Environmental Systems, ICES 2007 - Chicago, IL, United States Duration: Jul 9 2007 → Jul 12 2007 |
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ASJC Scopus subject areas
- Automotive Engineering
- Safety, Risk, Reliability and Quality
- Pollution
- Industrial and Manufacturing Engineering
Cite this
Testing heuristic tools for life support system analysis. / Rodriguez, Luis F; Jiang, Haibei; Bell, Scott; Kortenkamp, David.
In: SAE Technical Papers, 01.01.2007.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - Testing heuristic tools for life support system analysis
AU - Rodriguez, Luis F
AU - Jiang, Haibei
AU - Bell, Scott
AU - Kortenkamp, David
PY - 2007/1/1
Y1 - 2007/1/1
N2 - BioSim is a simulation tool which captures many basic life support functions in an integrated simulation. Conventional analyses can not efficiently consider all possible life support system configurations. Heuristic approaches are a possible alternative. In an effort to demonstrate efficacy, a validating experiment was designed to compare the configurational optima discovered by heuristic approaches and an analytical approach. Thus far, it is clear that a genetic algorithm finds reasonable optima, although an improved fitness function is required. Further, despite a tight analytical fit to data, optimization produces disparate results which will require further validation.
AB - BioSim is a simulation tool which captures many basic life support functions in an integrated simulation. Conventional analyses can not efficiently consider all possible life support system configurations. Heuristic approaches are a possible alternative. In an effort to demonstrate efficacy, a validating experiment was designed to compare the configurational optima discovered by heuristic approaches and an analytical approach. Thus far, it is clear that a genetic algorithm finds reasonable optima, although an improved fitness function is required. Further, despite a tight analytical fit to data, optimization produces disparate results which will require further validation.
UR - http://www.scopus.com/inward/record.url?scp=85072432041&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072432041&partnerID=8YFLogxK
U2 - 10.4271/2007-01-3225
DO - 10.4271/2007-01-3225
M3 - Conference article
AN - SCOPUS:85072432041
JO - SAE Technical Papers
JF - SAE Technical Papers
SN - 0148-7191
ER -