Border Crossing - Google Top Interview Questions
Problem Statement :
You are given two-dimensional lists of integers roads and countries as well as integers start and end.
Each element in roads contains [x, y, weight] meaning that to travel from city x to y costs weight. Each
element countries[i] represents all of the cities that belong to country i. Every city belongs to exactly
one country.
You are currently in city start and want to travel to city end. During this trip, you want to minimize
country-to-country border hops as a first priority, and then minimize total weight. Return a list of two
elements where the first is the number of country-to-country hops and the second element is the total
weight needed to make this trip. You can assume there is a solution.
Constraints
1 ≤ n ≤ 100,000 where n is the length of roads
Example 1
Input
roads = [
[0, 1, 1],
[1, 2, 1],
[0, 2, 4]
]
countries = [
[0],
[1],
[2]
]
start = 0
end = 2
Output
[1, 4]
Explanation
There are two paths from start to end, [0, 2] and [0, 1, 2]. [0, 2] crosses country boarder 1 time and has
total weight of 4. Path [0, 1, 2] crosses country boarders 2 times and has total weight of 3. Thus we
return [1, 4].
Example 2
Input
roads = [
[0, 1, 1],
[1, 3, 2],
[0, 2, 2],
[2, 3, 2]
]
countries = [
[0],
[1, 2],
[3]
]
start = 0
end = 3
Output
[2, 3]
Explanation
There are two paths from start to end, [0, 1, 3] and [0, 2, 3]. Path [0, 1, 3] crosses country boarders 2
times and has total weight of 3. Path [0, 2, 3] crosses country boarder 2 times and has total weight of 4.
Thus we return [2, 3].
Solution :
Solution in C++ :
vector<int> solve(vector<vector<int>>& roads, vector<vector<int>>& countries, int start, int end) {
int n = 0;
for (auto& road : roads) {
n = max(road[0], n);
n = max(road[1], n);
}
n++;
vector<vector<pair<int, int>>> graph(n);
vector<int> country(n);
for (int i = 0; i < (int)countries.size(); i++) {
for (auto& who : countries[i]) {
country[who] = i;
}
}
for (auto& road : roads) {
graph[road[0]].push_back({road[1], road[2]});
}
list<int> q;
q.push_back(start);
vector<pair<int, int>> cost(n);
for (int i = 0; i < n; i++) {
cost[i] = {INT_MAX, INT_MAX};
}
cost[start] = {0, 0};
while (!q.empty()) {
int curr = q.front();
q.pop_front();
for (auto& [v, w] : graph[curr]) {
int change = country[v] != country[curr];
if (cost[v].first > cost[curr].first + change) {
cost[v].first = cost[curr].first + change;
cost[v].second = cost[curr].second + w;
if (change) {
q.push_back(v);
} else {
q.push_front(v);
}
} else if (cost[v].first == cost[curr].first + change &&
cost[v].second > cost[curr].second + w) {
cost[v].second = cost[curr].second + w;
if (change) {
q.push_back(v);
} else {
q.push_front(v);
}
}
}
}
return {cost[end].first, cost[end].second};
}
Solution in Java :
import java.util.*;
class Solution {
public int[] solve(int[][] roads, int[][] countries, int source, int end) {
HashMap<Integer, List<int[]>> g = new HashMap<>();
for (int[] road : roads) {
int u = road[0];
int v = road[1];
if (!g.containsKey(u)) {
g.put(u, new ArrayList<>());
}
g.get(u).add(new int[] {v, road[2]});
}
HashMap<Integer, Integer> country = new HashMap<>();
for (int i = 0; i < countries.length; i++) {
for (int j : countries[i]) {
country.put(j, i);
}
}
PriorityQueue<int[]> pq = new PriorityQueue<>((p, q) -> {
return Long.compare(p[1] * (long) 1e12 + p[2], q[1] * (long) 1e12 + q[2]);
});
pq.add(new int[] {source, 0, 0});
HashSet<Integer> relaxed = new HashSet<>();
while (pq.size() > 0) {
int[] node = pq.poll();
if (node[0] == end) {
return new int[] {node[1], node[2]};
}
int u = node[0];
if (relaxed.contains(u))
continue;
relaxed.add(u);
if (g.containsKey(u)) {
for (int[] edge : g.get(u)) {
int v = edge[0];
pq.add(new int[] {v, node[1] + (country.get(u) != country.get(v) ? 1 : 0),
node[2] + edge[1]});
}
}
}
return new int[] {0, 0};
}
}
Solution in Python :
class Solution:
def solve(self, roads, countries, start, end):
cntry = defaultdict(int)
for i, arr in enumerate(countries):
for c in arr:
cntry[c] = i
adj = defaultdict(list)
for x, y, w in roads:
if cntry[x] != cntry[y]:
w += 10 ** 10
adj[x].append((y, w))
dist = defaultdict(lambda: 10 ** 20)
dist[start] = 0
visited = set()
h = [(0, start)]
while h:
d, city = heappop(h)
if city in visited:
continue
visited.add(city)
for c, w in adj[city]:
if dist[c] > d + w:
dist[c] = d + w
heappush(h, (d + w, c))
return dist[end] // 10 ** 10, dist[end] % 10 ** 10
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