Develop a Local Search algorithm for the problem and provide Pseudo code for your algorithm. Present the rationale of your algorithms in one paragraph followed by the Pseudo code. 6) Implement the Local Search Algorithm using a programming language of your choice. Combine the Greedy Algorithm and the Local Search Algorithm you designed into one program such that they run sequentially (start with a greedy solution and follow it by the Local Search for improvement). The data provided will be the input to the program and the output needs to be the items selected and the objective function value. Report the results of the greedy algorithm as well as the results of the combined algorithm (greedy and local search). Include the results of your program in the report by taking a snapshot of the programs output. 7) In your code and pseudo code, clearly label where one algorithm ends and the second starts. Make sure you define the notation you use in your pseudo code and keep in mind that the Pseudo code needs to be independent enough such that if you hand it to someone who does not know much about the problem, s/he can implement it into actual code. 8) Compare the results obtained using your algorithms to the optimal solution obtained in Question 2. Provide a meaningful metric(s) that can easily tell someone how good your algorithms are. Use the metric(s) to report how well the Greedy algorithm performed and how well the combined algorithm performed. 9) Determine the Order of the algorithm as a function of the problem size using the big-O notation. That is, decide the maximum number of steps that your greedy and local search algorithms take to solve a problem of size n.

v	C1	C2	C3	C4	C5	C6	C7	C8	C9	C10
100	8	8	3	5	5	5	0	3	3	3
600	12	12	6	10	13	13	0	0	2	2
1200	13	13	4	8	8	8	0	4	4	4
2400	64	75	18	32	42	48	0	0	0	8
500	22	22	6	6	6	6	8	8	8	8
2000	41	41	4	12	20	20	0	0	4	4
Capacity	80	96	20	36	44	48	10	18	22	24