[Bldg-sim] ISO Precedent paper in multi-objective optimization: statistical comparison of two pareto sets

karol.bandurski at put.poznan.pl karol.bandurski at put.poznan.pl
Thu Jul 15 04:41:39 PDT 2021


Dear Holly,

 

I am not sure if it is what you are looking for, but Team from Eindhoven
focused on robustness of Pareto front (so maybe it could be use to compare
robustness of two pareto fronts):

https://www.aivc.org/sites/default/files/P_1560.pdf

 

Kind regards,

Karol

 

---------------------------------------------------------------------------

Karol BANDURSKI Ph.D, Assistant Professor    

Faculty of Environmental and Energy Engineering 

Division of Heating, Air Conditioning and Air Protection 

Poznan University of Technology

 <https://www.researchgate.net/profile/Karol_Bandurski>
https://www.researchgate.net/profile/Karol_Bandurski

***

dr inż. Karol BANDURSKI, Adiunkt

Wydział Inżynierii Środowiska i Energetyki

Zakład Ogrzewnictwa, Klimatyzacji i Ochrony Powietrza

Politechnika Poznańska

 

 

 

From: Samuelson, Holly Wasilowski <hsamuelson at gsd.harvard.edu> 
Sent: Wednesday, July 14, 2021 4:48 PM
To: bldg-sim at lists.onebuilding.org
Cc: Salimi, Shide <ssalimi at gsd.harvard.edu>
Subject: [Bldg-sim] ISO Precedent paper in multi-objective optimization:
statistical comparison of two pareto sets

 

Dear Building Sim,

Can any of you recommend a precedent paper for us?  In short, we want to
compare two sets of optimal solutions in two different multi-objective
optimizations, to determine whether the characteristics of the two sets are
significantly different.

 

Longer version:

We set up a multi-objective analysis and found a set of optimal solutions
(buildings whose simulation results lie on the pareto front).  Then we did
this again for slightly different objectives, i.e. different comfort
criteria.  We now have two sets of "optimal" buildings. They have different
characteristics, like insulation levels and window-to-wall ratios.  We want
to determine if the differences between the two sets are significant. We
have ideas of how to analyze this, but it would be great to see how others
have done this in the past. This precedent research could be from any field
using optimization, not just building science.

 

If you have any leads for us, we'd appreciate it.

Thanks!

Holly

 

Holly W. Samuelson | DDes | Registered Architect

Associate Professor | Harvard Graduate School of Design

Co-Head MDes Energy and Environment Program

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