Here is the logic that I tried to use but failed to solve the problem:

array P is array of prison cells numbered from 0..N-1
array Q is array of prisoners to be released in order given in input
(sorted order)

First find out the the element in Q that is nearest to center of N.
for example if there are 10 prison cells (index 0..9) and Q contains
[3,6,9] then 6 is nearest to center of P (at index 5)
release prisoner 6 first that means we need to bribe 4 prisoners in
left side + 5 prisoners in right side.
there is now an empty cell at index 5. So we now have two subproblmes
P1=0..4 and P2=6..9 with Q=[3,9]
solve two subproblems recursively
return 4+5+answer(P1,Q) + answer(P2,Q)

But this logic returned 36 for the second test case instead of 35. I
couldn't figure out the problem in time. I need to know if the logic
is worth investigating more.

Regards,
KeJo

On Sep 15, 2:31 am, Luke Pebody <[email protected]> wrote:
> Here's my solution in Pascal:
>
> program hello;
> const
>    coder       = 'bozzball';
>
> var
>    N,i,j,P,Q,d,k : integer;
>    a             : array[0..101] of LongInt;
>    b             : array[0..101,0..101] of LongInt;
>
> begin
>    readln(N);
>    for i := 1 to N do
>    begin
>       readln(P,Q);
>       for j := 1 to Q do
>          read(a[j]);
>       a[0] := 0;
>       a[Q+1] := P+1;
>       for j := 0 to Q do
>          b[j][j+1] := 0;
>       for d := 2 to Q+1 do
>          for j := 0 to (Q+1-d) do
>          begin
>             b[j][j+d] := b[j][j+1] + b[j+1][j+d];
>             for k := j+2 to j+d-1 do
>                if (b[j][j+d] > (b[j][k] + b[k][j+d])) then
>                   b[j][j+d] := b[j][k] + b[k][j+d];
>             b[j][j+d] := b[j][j+d] + (a[j+d]-(a[j]+2));
>          end;
>       writeln('Case #', i, ': ', b[0][Q+1]);
>    end;
> end.
>
> On Mon, Sep 14, 2009 at 10:29 PM, Luke Pebody <[email protected]> wrote:
> > To solve the small case, you can simply try every possible ordering of
> > the at most 5 prisoner numbers. For any input case there are at most
> > 120 attempts to try.
>
> > While I was coding this, I noticed that after any particular prisoner
> > is released, the prisoners with a lower number and the prisoners with
> > a higher number cannot affect each other. Therefore, each
> > step breaks the problem down into *smaller subproblems* - the clear
> > sign that a problem could be handled by Dynamic Programming.
>
> > To that end, suppose that (as in the question), there are P prisoners,
> > and there are Q prisoners to be released, 0 < A_1 < ... < A_Q <= P.
>
> > To simplify the arguments, set A_0=0 and A_{Q+1}=P+1. (Suppose there
> > were prisoners on either side of the original P prisoners that have
> > already been released).
>
> > Then for 0 <= i < j <= Q+1, define ans_{i,j} to be the minimum
> > possible total bribe to release prisoners A_{i+1}, ..., A_{j-1} given
> > that prisoners A_i and A_j have been released.
>
> > Then the answer we are looking for is ans_{0,Q+1}.
>
> > To come up with an expression for ans_{i,j}, suppose that you first
> > release prisoner A_k where i < k < j. This release costs (A_j-A_i)-2
> > in bribes. After this release, cell A_k is empty.
> > Therefore, when you release any prisoners with numbers less than A_k,
> > you will not have to bribe any prisoners whose cell number is more
> > than A_k or vice versa.
> > Thus, (and this is the vital point), the releases of prisoners less
> > than A_k have no effect on the cost of the releases of prisoners more
> > than A_k or vice versa.
>
> > Thus, the minimum possible cost to release all of the prisoners
> > A_{i+1}, ..., A_{j-1}, given that you start with A_k is:
> >  * (A_j-A_i)-2 (the cost in bribes of releasing prisoner A_k)
> >  * ans_{i,k} (the cost to release the prisoners between A_i and A_k 
> > exclusive)
> >  * ans_{k,j} (the cost to release the prisoners between A_i and A_k 
> > exclusive).
>
> > To summarise: if i + 2 <= j, ans_{i,j} = (A_j-A_i)-2 + min(i < k < j)
> > ans_{i,k}+ans_{k,j}. If j = i+1, ans_{i,j} = 0 (there are no prisoners
> > between A_i and A_j to release).
>
> > The algorithm goes as follows:
> >  Let ans be a 2-dimensional array of size Q+2 by Q+2, initially filled with 
> > 0's.
> >  For di in the range 2 to Q+1 (inclusive):
> >  For i in the range 0 to Q+1-di (inclusive):
> >   Set j = di+i
> >   Set ans[i][j] = ans[i][i+1] + ans[i+1][j]
> >   For k in the range i+2 to j-1 (inclusive):
> >    If ans[i][j] > ans[i][k] + ans[k][j]:
> >     Set ans[i][j] = ans[i][k] + ans[k][j]
> >   (Now ans[i][j] = min(ans[i][k]+ans[k][j] for i < k < j))
> >   Increment ans[i][j] by (A_j-A_i)-2 (where A_0=0, A_{Q+1}=P+1 and
> > A_1, ..., A_Q are the numbers entered)
> >  The answer is Ans_{0,Q+1}.
>
> > In particular, for case #2: where P = 20, Q = 3 and A_1 = 3, A_2 = 6,
> > A_3 = 14 (so A_0 = 0 and A_4 = A_{Q+1} = P+1 = 21).
>
> > ans_{0,1} = 0
> > ans_{1,2} = 0
> > ans_{2,3} = 0
> > ans_{3,4} = 0
> > ans_{0,2} = (A_2-A_0)-2+min([ans_{0,1}+ans_{1,2}]) = 4
> > ans_{1,3} = (A_3-A_1)-2+min([ans_{1,2}+ans_{2,3}]) = 9
> > ans_{2,4} = (A_4-A_2)-2+min([ans_{2,3}+ans_{3,4}]) = 13
> > ans_{0,3} = (A_3-A_0)-2+min([ans_{0,1}+ans_{1,3},ans_{0,2}+ans_{2,3}])
> > = 12 + min(9,4) = 16
> > ans_{1,4} = (A_4-A_1)-2+min([ans_{1,2}+ans_{2,4},ans_{1,3}+ans_{3,4}])
> > = 16 + min(13,9) = 25
> > ans_{0,4} = 
> > (A_4-A_0)-2+min([ans_{0,1}+ans_{1,4},ans_{0,2}+ans_{2,4},ans_{0,3}+ans_{3,4}])
> > = 19 + min(25,17,16) = 35,
> > giving the answer 35 as stated in the problem.
>
> > On Mon, Sep 14, 2009 at 9:57 PM, Nikhil Mahajan <[email protected]> wrote:
>
> >> How did you solve this question? Can someone please explain an
> >> algorithm that could be used?
>
> >> Thanks.
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