Please help, I am stuck with the following programs in Python:

For problems 1 and 2, do the followin 1. Code a simple SA to solve the problem: encode the problem, develop the definition of a neighborhood, define a move operator, select an annealing schedule and select a stopping criterion. Run your SA. Perform the following changes on your SA code (one by one; not cumulative). Compare and summarize the results - change the initial starting solution five times - change the annealing schedule three times - change the stopping criterion three times - change the random number seed ten times 2. 3. 4. Include your own code (as appendix) with your homework 5. I am including the global optimum to each problem for reference purpose; do not use it in your solution methodology Problem 1 This is the fourth of the Quadratic Assignment Problem (QAP) test problems of Nugent et al. Eight departments are to be placed in eight locations with four in the top row and four in the bottom row. The objective is to minimize flow costs between the placed departments. The flow cost is (flow *distance), where both flow and distance are symmetric between any given pair of departments. Below is the flow and distance matrix where rectilinear distance is the upper half. The optimal flow costs is 107 (or 214 if you double the flows) Flow dist. 2 3 4567 8 6A2X0XS224 6 0 5100 4 4 3 21 0 2 0210 1 10 Problem 2 This is the "Himmelblau function" where x lies between 6 and y lies between 6, The objective is to minimize z. One of the global minima lies at (3.0000, 2.0000) where z 0.0000