Scilab Function

mine - a mining problem

### Calling Sequence

  `[cout,feed]=mine(n1,n2,uvect)`
  `[]=showcost(n1,n2,teta,alpha)`

### Parameters

- `n1` : Number of discrete point for the state.
- `n2` : Number of time step
- `uvect` : a row vector which gives the possible control value ( integer values ). for example `u=[-1,0,1]` means that at each step we come down one step or stay at the same level or rise one step ).
- `cout(n1,n2)` : The Bellman values.
- `feed(n1,n2)` : The feedback Law.

### Description

Dynamic programming applied to an optimal extraction of ore in an opencast mine. The extraction is done as follows : the steam shovel move forward for (k=1,2,...,n2) at each step it takes the ore, then move up or down (or stay at the same level) according to the control value to reach another level at next step. The extraction process must maximise the following cost :

       -- n2-1
       \
       /        f(x(k),k) + V_F(x,n2)
       -- k=1

with `x(k+1)=x(k) + u` . `x(k)` is the trajectory depth at step `k` (`x=1` is the ground level). The instantaneous cost `f(i,k)` stands for the benefit of digging at depth `i` at position `k` . It must be given as a Scilab macro `ff_o`

    [y]=ff_o(x,k)

and for efficiency `ff_o` must accept and return column vectors for `x` and `y` .

`V_F(i,n2)` is a final cost which is set so as to impose the steam shovel to be at ground level at position `n2`

`showcost` Shows a 3D representation of the instantaneous cost.