Friday, 15:45 - 16:10 h, Room: H 0107


Oleg Burdakov
An approach to solving decomposable optimization problems with coupling constraints

Coauthors: John C. Dunn, Mike Kalish


We consider a problem of minimizing f1(x)+f2(y) over
x ∈ X ⊆ Rn and y ∈ Y ⊆ Rm subject to
a number of extra coupling constraints of the form g1(x)g2(y) ≥ 0.
Due to these constraints, the problem may have a large number
of local minima.
For any feasible combination of signs of g1(x) and g2(y),
the coupled problem is decomposable, and the resulting two problems
are assumed to be easily solved.
An approach to solving the coupled problem is presented. We apply
it to solving coupled monotonic regression problems arising in
experimental psychology.


Talk 2 of the contributed session Fri.3.H 0107
"Decomposition and relaxation methods" [...]
Cluster 16
"Nonlinear programming" [...]


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