bv_cvxbook_extra_exercises

# If you use a change of variables be sure to explain

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Unformatted text preview: ime T ther as T ther = min{t | c(τ ) ≥ cmin for τ = t, . . . , T }, with T ther = ∞ if c(t) < cmin for t = 1, . . . , T . Here, cmin is the minimum concentration for the drug to have therapeutic value. Thus, T ther is the ﬁrst time at which the drug concentration reaches, and stays above, the minimum therapeutic level. Finally, we get to the problem. The optimization variables are the treatment formulation vectors a(1) , . . . , a(K ) . There are two objectives: T ther (which we want to be small), and K −1 J ch = k=1 a(k+1) − a(k) ∞ (which we also want to be small). This second objective is a penalty for changing the formulation amounts in the treatments. The rest of the problem concerns the speciﬁc instance with data given in the ﬁle time_release_form_data.m. This gives data for T = 168 (one week, starting from 8AM Monday morning), with treatments occuring 3 times each day, at 8AM, 2PM, and 11PM, so we have a total of K = 21 treatments. We have m = 6 formulations, with proﬁles with...
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## This note was uploaded on 09/10/2013 for the course C 231 taught by Professor F.borrelli during the Fall '13 term at Berkeley.

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