Scalable module from Tedford and Martins (2010)¶
The modules located in the scalable_tm directory offer a set of classes relative to the scalable problem introduced in the paper:
Tedford NP, Martins JRRA (2010), Benchmarking multidisciplinary design optimization algorithms, Optimization and Engineering, 11(1):159-183.
This scalable problem aims to minimize an objective function quadratically depending on shared design parameters and coupling variables, under inequality constraints linearly depending on these coupling variables.
A system discipline computes the constraints and the objective in function of the shared design parameters and coupling variables.
Strongly coupled disciplines¶
The coupling variables are the outputs of strongly coupled disciplines.
Each strongly coupled discipline computes a set of coupling variables linearly depending on local design parameters, shared design parameters, coupling variables from other strongly coupled disciplines, and belonging to the unit hypercube.
This problem is said “scalable” because several sizing features can be chosen by the user:
the number of local design parameters for each discipline,
the number of shared design parameters,
the number of coupling variables for each discipline,
the number of disciplines.
A given sizing configuration is called “scaling strategy” and this scalable module is particularly useful to compare different MDO formulations with respect to the scaling strategy.
The scalable problem¶
TMScalableProblem class instantiates the disciplines of the
problem, that are
TMMainDiscipline and several
as well as the
These instantiated objects can be used in a
The scalable study¶
TMScalableStudy class instantiates a
for a particular scaling strategy
where the number of local design parameters is the same for all disciplines
as well as the number of coupling variables.
It provides a method to run MDO formulations and graphical capabilities
to analyze the results.
The parametric scalable study¶
TMParamSS class instantiates several
associated with different scaling strategies, e.g. different numbers of local
design parameters or different numbers of coupling variables.
It provides a method to run MDO formulations and save results on the disk.
TMParamSSPost provides graphical capabilities to post-process
these saved results.