Given: n = the number of houses

t = number of towers

A[] = list of the locations of each house

Output: Determine the optimal antenna range for each tower using DYNAMIC PROGRAMMING.

For example, consider a town called Townsville with 4 houses positioned at 0.2, 0.5, 1.5 and 2.2 with 2 base station antennas to be set up. The optimum antenna range for this given town plan is 0.35 which can be achieved by setting up the antennas at positions 0.35 and 1.85. This example can be better visualized with the illustration below. H1 H2 H3 0 0.2 0.5 1.5 2 2.2 Ho H1 H2 H3 0 0.2 0.35 0.5 1.5 1.85 2 2.2 Hint: The problem might make you scratch your head, but it isn't as difficult as it seems! Think of the possible subproblems that could be used. You could construct a n x k table indexed Y[1.jl that stores the optimal antenna range for the subproblems and another indexed c[t, j] that stores a set of base stations for the subproblems. What can these sub-problems represent? For example, consider a town called Townsville with 4 houses positioned at 0.2, 0.5, 1.5 and 2.2 with 2 base station antennas to be set up. The optimum antenna range for this given town plan is 0.35 which can be achieved by setting up the antennas at positions 0.35 and 1.85. This example can be better visualized with the illustration below. H1 H2 H3 0 0.2 0.5 1.5 2 2.2 Ho H1 H2 H3 0 0.2 0.35 0.5 1.5 1.85 2 2.2 Hint: The problem might make you scratch your head, but it isn't as difficult as it seems! Think of the possible subproblems that could be used. You could construct a n x k table indexed Y[1.jl that stores the optimal antenna range for the subproblems and another indexed c[t, j] that stores a set of base stations for the subproblems. What can these sub-problems represent