e-olymp 93. Truck driving

Task

Umidsh Izadish is a truck driver and wants to drive from a city to another city while there exists a dedicated straight road between each pair of cities in that country. Amount of consumed fuel is the distance between two cities which is computed from their coordinates. There is a gas station in each city, so Umidsh can refuel the gas container of his truck. Your job is to compute the minimum necessary volume of gas container of Umidsh’s Truck.

Input data

The first line of input contains an integer, the number of test cases. Following, there are data for test cases. Each test case begins with a line containing one integer, $C$ $(2 ≤ C ≤ 200)$, which is the number of cities. The next $C$ lines each contain two integers $x$, $y$ $(0 ≤ x, y≤ 1000)$ representing the coordinate of one city. First city is the source city and second is the destination city of Umidsh.

Output data

There should be one line for each test case in output. Each line should contain one floating point number which is the minimum necessary volume of truck’s gas container, printed to three decimals.

Tests

Input Output
$2$
$2$
$0$ $0$
$3$ $4$
$3$
$17$ $4$
$19$ $4$
$18$ $5$
$5.000$
$1.414$
$1$
$3$
$4$ $5$
$4$ $6$
$4$ $7$
$1.000$
$2$
$4$
$0$ $1$
$0$ $-1$
$1$ $0$
$-1$ $0$
$3$
$8$ $9$
$0$ $1$
$14$ $14$
$1.414$
$11.314$
$3$
$2$
$1$ $1$
$1$ $2$
$5$
$8$ $6$
$3$ $3$
$4$ $1$
$7$ $7$
$5$ $0$
$3$
$1$ $1$
$1$ $3$
$2$ $5$
$1.000$
$5.657$
$2.000$

Code

Solution

We can interpretate the set of the cities as weighted graph, which vertices represent cities and weight of each edge between two vertices is the gas volume required for passing the distance between corresponding cities.
The volume of truck’s gas container depends on the gas volume required for arrival to the each next station of the Umidsh’s way. The maximum between gas volume required to get to the city $A$ and gas volume required to pass the way from the city $A$ to the city $B$ represents the minimum necessary gas volume required to get to the city $B$ through the city $A$. So the volume of truck’s gas container would turn to minimum, when the maximum gas volume required for passing the distance between each two stations of his way would turn to minimum. Thus we could use modified Dijkstra’s algorithm to find the biggest value among the weights of an edges between each two stations of the way between vertice 0 and vertice 1.

References

The task at E-Olymp
My solution at ideone

e-olymp 2267. Journey

The army of Rzeczpospolita is moving from the city Kostroma to the village Domnino. Two hetmans, Stefan and Konstantin, lead the army.

Stefan procured the roadmap of Kostroma province, and every night he routes the army from one village to the other along some road. Konstantin bought the map of secret trails between villages in advance, and every day he leads the march along the one of such trails. Each hetman asks their guide Ivan Susanin for a route before each march.

The length of each road is indicated on Stefan’s map. So Stefan knows the minimal distance from each village to the Domnino village according to his map. Similarly Konstantin knows the minimal distance from each village to Domnino village along trails on his map.

Ivan Susanin does not want to be disclosed as a secret agent, so each time he chooses a road (for Stefan) or a trail (for Konstantin) so, that the minimal distance to the Domnino village according to the map owned by the asking hetman is strictly decreasing.
Maps
Help Ivan to find the longest possible route to the Domnino village.

Input

The first line contains three integer numbers [latex]n, s[/latex] and [latex]t[/latex] — number of villages in Kostroma province, and numbers of start and Domnino village [latex](2 \le n \le 1000; 1 \le s; t \le n)[/latex]. Villages are numbered from [latex]1[/latex] to [latex]n[/latex]. Start and Domnino villages are distinct.

Two blocks follow, the first one describing Stefan’s map, and the second one describing Konstantin’s map.

The first line of each block contains an integer number [latex]m[/latex] — the number of roads/trails between villages [latex](n-1 \le m \le 100000)[/latex]. Each of the following [latex]m[/latex] lines contains three integer numbers [latex]a, b[/latex], and [latex]l[/latex] — describing the road/trail between villages [latex]a[/latex] and [latex]b[/latex] of length [latex]l[/latex] [latex](1 \le a, b \le n; 1 \le l \le 10^6)[/latex].

Rzeczpospolita army can move in any direction along a road or a trail. It’s guaranteed that one can travel from any village to any other using each of the maps. The army starts its movement in the evening from the village number and moves one road each night and one trail each day.

Output

Output the total length of the longest route that Ivan Susanin can arrange for Rzeczpospolita army before reaching the Domnino village (along the roads and trails). If Ivan Susanin can route the army forever without reaching the Domnino village, output the number «[latex]-1[/latex]».

Tests

Input Output
1 5 1 5
5
1 2 2
1 4 2
2 3 1
3 4 1
5 3 1
4
1 2 2
2 4 2
2 3 1
2 5 2
-1
2 3 1 3
4
1 2 10
2 3 10
1 3 20
2 3 30
4
2 1 10
1 3 10
1 1 10
2 3 10
20

Algorithm

The problem has been resolved together with Sploshnov Kirill.

So, we are dealing with a rather cumbersome task for the graphs, therefore we analyze it consistently. To get started we define the data structure

because dealing with the routes and subsequently, we will have to color our edges. For convenience, we don’t think about two maps as about different graphs, and can establish one graph, where edges of each map are painted in a different color.
For example edges of first map color in RED, and the other in BLUE. Then select the first map is equivalent to passing by red edges, or blue otherwise. In this way, route, that we are looking for, should be based on the successively alternating colors of the edges.
Proceed directly to the solution.
From the condition is understandable, that each hetman knows the shortest path to the final village. This data will be needed for us too, so for each map (edges of the same color) use Dijkstra’s algorithm and find the shortest path from each vertex to the target.  (Function   void djikstra(vector<Route>* graph, int* distancesInColoredGraph, unsigned int quantityOfAllVertices, int finishVertex, int color); ).  We need absolutely standard Dijkstra’s algorithm with the only difference that the edges of the opposite color aren’t available. You can learn more about Dijkstra’s algorithm in the sources of information listed at the end of the article.
Continue analyzing the condition, we understand, that we can’t pass over the edges so, that the shortest distance to the final vertex increased. This will help us to simplify the graph, and significantly reduce the number of possible variants of passage, namely, any bidirectional edge will be either removed completely or strictly directed.  Then, passing on to the edges of the same color in each map, if it doesn’t satisfy the specified condition coloring it as DELETED. (Function  void simplify(vector<Route>* graph, int* distance, unsigned int quantityOfAllVertices, int color); ).
Now we can get started with the search for the longest route. There are two options: either there is the longest path, or we can walk along the edges infinitely, if it does not contradict the statement of the problem, that is, in the combined of two maps graph there is a cycle. So we organize checks on acyclic. Now we have the right to pass along the edges only alternating colors at each step. In order to find a cycle, we use vertex coloring, and will explore the graph until we try to treat already colored vertex or not conclude that it is acyclic.  (Function  bool cyclicDFS(vector<Route>* graph, int* passedInRedGraph, int* passedInBlueGraph, int currentVertex, int color); ). This algorithm can be obtained after detailed acquaintance with the usual cycle searching algorithm (reference to the source is located at the end of the article). If we find any loop in this graph, then our job is over and we should just output «[latex]-1[/latex]».
Otherwise, make sure that the graph is acyclic, we are looking for the longest route. As our graph has been simplified and has no cycles, and all edges are directed, then the task of finding this way becomes computationally simple. For this declaring an array of longest distance dynamically, along the way memorizing the already calculated values, sequentially find the maximum length of the route until we arrive at the finish village. (Function  int maxDistDFS(vector<Route>* graph, int* maxDistancesInRedGraph, int* maxDistancesInBlueGraph, int currentVertex, int color) ). This will be the answer to the task.

Rest details of the implementation can be found in the code of the program or in the sources of information listed at the end of the article.

Code

Links

e-olymp 4002. Down with cheating!

During the test, Professor Floyd noticed that some students exchanged notes. At first, he wanted to put a bad mark everyone, but that day the professor was in a good mood, therefore he decided to split all the students into two groups and put a bad mark to only those,who writting off.
The professor recorded all the pairs of students, who exchanged notes. You need to determine whether they can be divided into two groups, where student of one group exchange notes only with student of other group.

Input

There are two numbers in first line [latex]m[/latex] and [latex]n[/latex] — quantity of students and quantity of pairs, who exchanged notes. [latex](1 \le n \le 100[/latex], [latex]0 \le m \le n(n-1)/2)[/latex]. Further in [latex]m[/latex] lines there are description of student pairs: two different numbers, corresponding to the student serial number, who exchanged notes (numbering from [latex]1[/latex]). Each pair of students is listed only once.

Output

Print the answer to the Professor’s Floyd task. If it is possible to divide the students into two groups output «YES», or «NO» otherwise.

Test

Input Output
1 3 2
1 2
2 3
YES
2 3 3
1 2
1 3
2 3
NO
3 12 9
1 3
2 3
4 5
5 6
6 8
6 9
7 9
8 10
11 12
YES
4 12 10
1 3
2 3
4 5
5 6
6 8
6 9
7 9
8 9
8 10
11 12
NO

bipartite graph
Illustration for the test №3notBipartiteGraph
Illustration for the test №4
 

Algorithm

After reading the statement of the problem becomes clear that our goal is to determine whether it is possible to divide the graph into two sets in each of them there aren’t adjacent vertices — check whether the graph is bipartite.
For the implementation, we need a basic function
bool isBipartite(vector<int> *listOfVertices, int *colorOfVertices, int sourceVertex, int quantityOfVertex), that takes a graph (in this program as an array of vectors of adjacent vertices, but can be done similar implementation on the adjacency matrix), array of vertices’ colors, vertex, which we start checking, and the number of vertices.
To solve the problem we perform graph coloring. Naturally, we organize data reading process. And our next sequence of steps is:

  • Initially, we define all the vertices as WHITE — not processed.
  • Call the fucntion for the first vertex (in our numbering — zero).
  • Assign source vertex with one of the colors (for convenience in program we denote it as RED) — equivalent to the action that we put the vertex in the first of two sets.
  • Color all adjacent vertex with inverse color (in program it’s BLUE — has opposite to RED number value) — equivalent to the action that we put vertices in the second set.
  • Color all adjacent to the adjacent vertices with RED color —  we put them in the first set.
  • Repeat this until we have completed bypassing (for convenience we use queue)  — coloring of all connected vertices. But we can find adjacent vertices with same color that sygnalize that our graph cannot be colored with two color — so it isn’t bipartite.

It should be noted that the function implemented in such way works for only one connected component. Therefore, to check the disconnected graphs we must check  all vertices which color is white.

Code

 

Links