Consider the optimization problem of minimizing a function f(x) over a standard from polyhedron. When f(x) is linear, one method of solution is to employ the Primal Path Following Algorithm (discussed in class and in Section 9.4 of the textbook). Now, suppose f(x) is not linear, but is twice continuously differentiable. Can the same algorithm still be used to solve this new problem? Carefully discuss some possible outcome

No,due to continuously double differentiable,this algorithm will not solve this problem as function is linear.  

function 2 has a greater rate of change than function 1

function 2 has a greater y-intercept than function 1

step-by-step explanation:

30 miles

step-by-step explanation:

we know that 60 seconds equals 1 minute and 60 minutes 1 hour

44 ft       60 sec     60 min     158400   ft

  *   *   =

1 sec       1 min       1 hour         hour

we know that there are 5280 ft per mile

158400   ft       1 mile         30 miles

  *   =

1   hour               5280 ft     1 hour

so in 1 hour   it can travel 30 miles