Heuristics in Optimization Homework help me please

The bubble sort (or adding two nxn matrices) take O(n2 ) unit operations. However, set partitioning, knapsack and some versions of TSP can be solved in O(2n ) complexity. On the other hand, single machine total tardiness problem can be solved optimally using a brute force approach in O(n!) time. Suppose that you are required to solve the above problems by using these three algorithms with the complexities of n2 , 2n , and n!. Given a computer with a CPU that makes 109 operations per second, what are the worst case running times of these algorithms for the problem sizes of 10, 15, 20, 30, 50, 100, 101, 1000, 1001 and 1000000? Report the solutions in terms of seconds, minutes, hour, days, years or centuries. Now assume that a magnificent development has taken place in the computer hardware technology that resulted in billion (109 ) times faster CPUs. Furthermore, it is possible to combine a million CPUs in parallel (i.e., parallel processing). After all, if humankind can get a computational power in the magnitude of 1024 operations per second, what is the running time of these algorithms above? Generally speaking, does the time complexity depend on technology?

n=	10	15	20	30	50	100	101	1000	1001	10^6
n^2
2^n										x
n!								x	x	x

Explain your calculations clearly.