Algorithm Analysis 1. What is the smallest value of n such that an algorithm whose running time is 100n^2 runs faster than an algorithm whose running time is 2^n on the same machine?

Game of 8 queens.Algorithmic solutions to the problems must be generated, with each of the following algorithm design techniques, in the Python language. Greedy Algorithms, Dynamic Programming, Bactracking, Branch and Bound.Calculate and analyze the complexity t(n) of each algorithm.Perform average comparison (minimum 3 executions with the same data pool) of time and memory consumption for each technique and algorithm.Given a chess board of size nxn, find the way(s) to place n queens, without any of them threatening each other.

1. Prepare an excel table to compute the runtime for four different algorithms for solving the same problem, for value of N ranging from N= 10 to 100 in steps of 10 and then determine the best and worst algorithm. The runtimes of the algorithms are given as below: T₁(N) = (1.2) T₂(N) = 3N³ + 200 T₂(N) = NIgN T4(N) = 100N Make sure to attach the excel spread sheet. Also, may be worth to plot the function on excel chart (line plot) and you can show the functions growth.

Can you answer this question again? In the first attempt algorithms time complexity is given to be O(n^3) and now it is changed as O(n^2). What is the best algorithm, code and time complexity to this question?

Computer science