I have problem with my homework.
Given a board of dimensions m
x n
is given, cut this board into rectangular pieces with the best total price. A matrix gives the price for each possible board size up through the original, uncut board.
Consider a 2 x 2
board with the price matrix:
3 4
3 6
We have a constant cost for each cutting for example 1
.
Piece of length 1 x 1
is worth 3
.
Horizontal piece of length 1 x 2
is worth 4
.
Vertical piece of length 1 x 2
is worth 3
.
Whole board is worth 6
.
For this example, the optimal profit is 9, because we cut board into 1 x 1
pieces. Each piece is worth 3
and we done a 3
cut, so 4 x 3
- 3 x 1
= 9
.
Second example:
1 2
3 4
Now I have to consider all the solutions:
4
1x1
pieces is worth 4x1 - (cost of cutting) 3x1 = 1
2
horizontal 1x2 is worth 2x2 - (cost of cutting) 1x1 = 3
2
vertical 1x2 is worth 3x2 - (cost of cutting) 1x1 = 5
-> best optimal profit
1
horizontal 1x2 + 2 x (1x1) pieces is worth 2 + 2 - (cost of cutting) 2 = 2
1
vertical 1x2 + 2 x (1x1) pieces is worth 3 + 2 - (cost of cutting) 2 = 3
I've read a lot about rod cutting algorithm but I don't have any idea how to bite this problem.
Do you have any ideas?
I did this in Python. The algorithm is
best_val
= value of current board
- check each horizontal and vertical cut for better value
- for cut point <= half the current dimension (if none, return initial value)
- recur on the two boards formed
- if sum of values >
best_val
- ...
best_val
= that sum
- ... record cut point and direction
- return result: best_val, cut point, and direction
I'm not sure what you'll want for return values; I gave back the best value and tree of boards. For your second example, this is
(5, [[2, 1], [2, 1]])
Code, with debugging traces (indent
and the labeled print
s):
indent = ""
indent_len = 3
value = [[1, 2],
[3, 4]
]
def best_cut(high, wide):
global indent
print indent, "ENTER", high, wide
indent += " " * indent_len
best_val = value[high-1][wide-1]
print indent, "Default", best_val
cut_vert = None
cut_val = best_val
cut_list = []
# Check horizontal cuts
for h_cut in range(1, 1 + high // 2):
print indent, "H_CUT", h_cut
cut_val1, cut_list1 = best_cut(h_cut, wide)
cut_val2, cut_list2 = best_cut(high - h_cut, wide)
cut_val = cut_val1 + cut_val2
if cut_val > best_val:
cut_list = [cut_list1, cut_list2]
print indent, "NEW H", h_cut, cut_val, cut_list
best_val = cut_val
cut_vert = False
best_h = h_cut
# Check vertical cuts
for v_cut in range(1, 1 + wide // 2):
print indent, "V_CUT", v_cut
cut_val1, cut_list1 = best_cut(high, v_cut)
cut_val2, cut_list2 = best_cut(high, wide - v_cut)
cut_val = cut_val1 + cut_val2
if cut_val > best_val:
cut_list = [cut_list1, cut_list2]
print indent, "NEW V", v_cut, cut_val, cut_list
best_val = cut_val
cut_vert = True
best_v = v_cut
# Return result of best cut
# Remember to subtract the cut cost
if cut_vert is None:
result = best_val , [high, wide]
elif cut_vert:
result = best_val-1, cut_list
else:
result = best_val-1, cut_list
indent = indent[indent_len:]
print indent, "LEAVE", cut_vert, result
return result
print best_cut(2, 2)
Output (profit and cut sizes) for each of the two tests:
(9, [[[1, 1], [1, 1]], [[1, 1], [1, 1]]])
(5, [[2, 1], [2, 1]])
Let f(h,w)
represent the best total price achievable for a board with height h
and width w
with cutting price c
. Then
f(h,w) = max(
price_matrix(h, w),
f(i, w) + f(h - i, w) - c,
f(h, j) + f(h, w - j) - c
)
for i = 1 to floor(h / 2)
for j = 1 to floor(w / 2)
Here's a bottom-up example in JavaScript that returns the filled table given the price matrix. The answer would be in the bottom right corner.
function f(prices, cost){
var m = new Array(prices.length);
for (let i=0; i<prices.length; i++)
m[i] = [];
for (let h=0; h<prices.length; h++){
for (let w=0; w<prices[0].length; w++){
m[h][w] = prices[h][w];
if (h == 0 && w == 0)
continue;
for (let i=1; i<(h+1>>1)+1; i++)
m[h][w] = Math.max(
m[h][w],
m[i-1][w] + m[h-i][w] - cost
);
for (let i=1; i<(w+1>>1)+1; i++)
m[h][w] = Math.max(
m[h][w],
m[h][i-1] + m[h][w-i] - cost
);
}
}
return m;
}
$('#submit').click(function(){
let prices = JSON.parse($('#input').val());
let result = f(prices, 1);
let str = result.map(line => JSON.stringify(line)).join('<br>');
$('#output').html(str);
});
<script src="https://ajax.googleapis.com/ajax/libs/jquery/2.1.1/jquery.min.js"></script>
<textarea id="input">[[3, 4],
[3, 6]]</textarea>
<p><button type="button" id="submit">Submit</button></p>
<div id="output"><div>
Some thoughts on the problem rather than an answer:
It was a long time ago i studied dynamic programming, but i wrote up the following pseudo code which is think is O(n^2):
// 'Board'-class not included
val valueOfBoards: HashMap<Board, int>
fun cutBoard(b: Board, value: int) : int {
if (b.isEmpty()) return 0
if (valueOfBoards[b] > value) {
return 0;
} else {
valueOfBoards[b] = value
}
int maxValue = Integer.MIN_VALUE
for (Board piece : b.getPossiblePieces()) {
val (cuttingCost, smallerBoard) = b.cutOffPiece(piece)
val valueGained: int = piece.getPrice() - cuttingCost
maxValue = Max(maxValue, valueGained + cutBoard(smallerBoard, value + valueGained))
}
return maxValue;
}
The board class is not trivially implemented, here is some elaboration:
// returns all boards which fits in the current board
// for the initial board this will be width*height subboards
board.getPossiblePieces()
// returns a smaller board and the cutting cost of the cut
// I can see this becoming complex, depends on how one chooses to represent the board.
board.cutOffPiece(piece: Board)
It is not clear to me at the moment if cutOffPiece()
breaks the algorithm in that you do not know how to optimally cut. I think since the algorithm will proceed from larger pieces to smaller pieces at some point it will be fine.
I tried to solve the re computation of sub problems (identical boards) by storing results in something like HashMap<Board, price>
and comparing the new board with the stored best price before proceeding.
According to your answers I've prepared bottom-up and top-down implementation.
Bottom-up:
function bottomUp($high, $wide, $matrix){
$m = [];
for($h = 0; $h < $high; $h++){
for($w = 0; $w < $wide; $w++){
$m[$h][$w] = $matrix[$h][$w];
if($h == 0 && $w == 0){
continue;
}
for($i = 1; $i < ($h + 1 >> 1) + 1; $i++){
$m[$h][$w] = max(
$m[$h][$w],
$m[$i - 1][$w] + $m[$h - $i][$w] - CUT_COST
);
}
for($i = 1; $i < ($w + 1 >> 1) + 1; $i++){
$m[$h][$w] = max(
$m[$h][$w],
$m[$h][$i - 1] + $m[$h][$w - $i] - CUT_COST
);
}
}
}
return $m[$high-1][$wide-1];
}
Top-down:
function getBestCut($high, $wide, $matrix){
global $checked;
if(isset($checked[$high][$wide])){
return $checked[$high][$wide];
}
$bestVal = $matrix[$high-1][$wide-1];
$cutVert = CUT_VERT_NONE;
$cutVal = $bestVal;
$cutList = [];
for($hCut = 1; $hCut < 1 + floor($high/2); $hCut++){
$result1 = getBestCut($hCut, $wide, $matrix);
$cutVal1 = $result1[0];
$cutList1 = $result1[1];
$result2 = getBestCut($high - $hCut, $wide, $matrix);
$cutVal2 = $result2[0];
$cutList2 = $result2[1];
$cutVal = $cutVal1 + $cutVal2;
if($cutVal > $bestVal){
$cutList = [$cutList1, $cutList2];
$bestVal = $cutVal;
$cutVert = CUT_VERT_FALSE;
$bestH = $hCut;
}
$checked[$hCut][$wide] = $result1;
$checked[$high - $hCut][$wide] = $result2;
}
for($vCut = 1; $vCut < 1 + floor($wide/2); $vCut++){
$result1 = getBestCut($hCut, $vCut, $matrix);
$cutVal1 = $result1[0];
$cutList1 = $result1[1];
$result2 = getBestCut($high, $wide - $vCut, $matrix);
$cutVal2 = $result2[0];
$cutList2 = $result2[1];
$cutVal = $cutVal1 + $cutVal2;
if($cutVal > $bestVal){
$cutList = [$cutList1, $cutList2];
$bestVal = $cutVal;
$cutVert = CUT_VERT_TRUE;
$bestH = $vCut;
}
$checked[$hCut][$vCut] = $result1;
$checked[$high][$wide - $vCut] = $result2;
}
if($cutVert == CUT_VERT_NONE){
$result = [$bestVal, [$high, $wide]];
}else if($cutVert == CUT_VERT_TRUE){
$result = [$bestVal - CUT_COST, $cutList];
}else{
$result = [$bestVal - CUT_COST, $cutList];
}
return $result;
}
Please tell me are they correct implementation of this method?
I wonder if time complexity is O(m^2*n^2)
in top-down method?