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Material Type: Assignment; Class: Nonlinear Optimization; Subject: Industrial & Systems Engr; University: Georgia Institute of Technology-Main Campus; Term: Spring 2003;
Typology: Assignments
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Problem 1 Nocedal and Wright, Problem 5.
Problem 2 Nocedal and Wright, Problem 5.
Problem 3 Nocedal and Wright, Problem 5.
Problem 4 Consider a symmetric positive definite matrix Q ∈ Rn×n, and the associated norm ‖x‖Q :=
xT^ Qx. Consider Q-conjugate directions d 0 , d 1 ,... , dn− 1 ∈ Rn^ generated from linearly independent vectors p 0 , p 1 ,... , pn− 1 ∈ Rn. Show that, for each k = 1,... , n − 1, dk = pk − pˆk, where ˆpk is the projection of pk onto the subspace spanned by p 0 ,... , pk− 1 (or the subspace spanned by d 0 ,... , dk− 1 ) with respect to the ‖ · ‖Q-norm, that is,
pˆk = arg min {‖pk − p‖Q : p ∈ [p 0 ,... , pk− 1 ]}
That is, dk is the part of pk that remains after we subtract the projection of pk onto the subspace spanned by p 0 ,... , pk− 1.