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Drop heuristic to improve runtime #2

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Drop heuristic to improve runtime #2

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16 changes: 6 additions & 10 deletions src/year2023/day17.rs
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Original file line number Diff line number Diff line change
@@ -5,8 +5,8 @@
//! is a great introduction to this algorithm.
//!
//! The heuristic is the [Manhattan distance](https://en.wikipedia.org/wiki/Taxicab_geometry)
//! to the bottom right corner. This will never overestimate the actual distance which is an
//! essential characteristic in the heuristic.
//! to the bottom right corner. Unfortunately, it costs more than it helps, since we essentially
//! need to explore the entire map anyways, so it's better not to use it.
//!
//! A crucial insight speeds things up. We only needs to store `(position, direction)` pairs in
//! the map of previously seen costs and do not also need to store the number of steps.
@@ -69,10 +69,6 @@ fn astar<const L: usize, const U: usize>(grid: &Grid<u32>) -> u32 {
let index = width * y + x;
let steps = cost[index][direction];

// The heuristic is used as an index into the bucket priority queue.
let heuristic =
|x: usize, y: usize, cost: u32| (cost as usize + width - x + height - y) % 100;

// Check if we've reached the end.
if x == width - 1 && y == height - 1 {
return steps;
@@ -102,7 +98,7 @@ fn astar<const L: usize, const U: usize>(grid: &Grid<u32>) -> u32 {
steps += heat[index];

if i >= L && (cost[index][1] == 0 || steps < cost[index][1]) {
todo[heuristic(x - i, y, steps)].push((x - i, y, 1));
todo[(steps as usize) % 100].push((x - i, y, 1));
cost[index][1] = steps;
}
}
@@ -122,7 +118,7 @@ fn astar<const L: usize, const U: usize>(grid: &Grid<u32>) -> u32 {
steps += heat[index];

if i >= L && (cost[index][1] == 0 || steps < cost[index][1]) {
todo[heuristic(x + i, y, steps)].push((x + i, y, 1));
todo[(steps as usize) % 100].push((x + i, y, 1));
cost[index][1] = steps;
}
}
@@ -144,7 +140,7 @@ fn astar<const L: usize, const U: usize>(grid: &Grid<u32>) -> u32 {
steps += heat[index];

if i >= L && (cost[index][0] == 0 || steps < cost[index][0]) {
todo[heuristic(x, y - i, steps)].push((x, y - i, 0));
todo[(steps as usize) % 100].push((x, y - i, 0));
cost[index][0] = steps;
}
}
@@ -164,7 +160,7 @@ fn astar<const L: usize, const U: usize>(grid: &Grid<u32>) -> u32 {
steps += heat[index];

if i >= L && (cost[index][0] == 0 || steps < cost[index][0]) {
todo[heuristic(x, y + i, steps)].push((x, y + i, 0));
todo[(steps as usize) % 100].push((x, y + i, 0));
cost[index][0] = steps;
}
}