Ecos3022 Vectors and Optimization Exercises 2022
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Vectors and Optimization Exercises
1. Vectors. Let vector a = (1; 2) and vector b = (1; 0): Plot these vectors on (x1 ;x2 ) space. Calculate vectors c = a + b and d = b 一 a: Plot these vectors on the same diagram. Are any of the vectors, a;b;c;d orthogonal to each other? Calculate the scalar products of the corresponding vectors to prove your answer.
2. Vectors. Let vector a = (1; 2; 3) and vector b = (2; 一1; 3): Calculate vectors c = a + b; and d = a 一 b and scalar products of vectors
a · b
a · c
b · c
3. Vectors and matrices. Consider vector a = (1; 一1) and matrix B = ┌ 3(2) 1(1) ┐ : Note that a\ = 2━(1)1、: This operation is called t|α}sp#se, the notation is a\ ; (or aT ) turns a string vector into the column vector and a column vector into the string vector. Calculate a · B (this should be a vector of size 1 X 2) and B · a\ (this should be a vector of size 2 X 1). Calculate scalar products a · a\ (this should be a number) and a\ · a (this should be a 2 X 2 matrix).
4. Di§erentiate the following functions
(a) f (x) = 3x2
(b) f (x) = 北2(3)
(c) f (x) = ae北
(d) f (x) = 1 ━e北 —。
(e) f (x) = aln(x)
(f) f (x) = h(g (x))
(g) f (x;y) = 3x3 + y2
5. Implicit functions 1. Take the budget equation
p1 x1 + p2 x2 = w
Find the slope of the implicit function x1 (x2 ). Show your work.
6. Optimization 1. A consumer seeks to maximise her utility by choosing how much of commodities A and B to consume. Let xA and xB denote the quantities demanded, and (pA ;pB ) the prices. Our consumer has utility
u(xA ;xB ) = ln(1 + xA ) + ln(1 + xB );
and she is subject to the budget constraint
xApA + xBpB = M
(a) Find the optimal bundle (xA ;xB ):
(b) How does the level of utility u(xA ;xB ) change when the consumerís income M changes? Relate this to the value of the Lagrange multiplier.
7. Optimization 2. You need to enclose a rectangular Öeld with a fence. You have
100 meters of fencing material. Determine the dimensions of the Öeld that will enclose the lα|gest α|eα . Set this up as a constrained optimization problem and approach this with Lagrangean. Hints: use all the information to determine the objective function and the constraint. It may help to draw. Recall: What is the area of a rectangle? Call the short side x and the long one y. What is the perimeter of such rectangle?
8. Optimization with inequality constraints. Find
maxf (x;y) = xy
s.to. x + y2 ≤ 2
x S 0;y S 0
Approach this formally via Lagrangean. Write all the Karush-Kuhn-Tucker condi- tions. Argue that the non-negativity constraints will not bind and that the x+y2 ≤ 2 constraint will hold as equality. Solve the resulting system of equations.
2023-04-15