Uva 10765 - Doves and bombs

  1  /*
  2  Problem link
  3  Type: Graph - Find articulation points
  4  Algorithm:

UVA 10092 - The Problem with the Problem Setter

  1  /*
  2  Problem link
  3  Type: Graph - Maximum Flow
  4  Algorithm:

UVa 11747 - Heavy Cycle Edges

  1  /*
  2  Problem type: Graph - MST
  3  Algorithm: Find the Minimum Spanning Tree (MST) (using Kruskal,
  4      Prim) and print out all the edges which are not included in the MST.
  5  */

UVa 10020 - Minimal coverage

  1 /*
  2  Problem link
  3  Type: Greedy - INTERVAL COVERING
  4  Algorithm:

UVa 11565 - Simple Equations

 1  /*
 2  Problem link
 3  Type: Complete Search
 4  Algorithm:

UVa 154 - Recycling

 1  /*
 2  Problem link
 3  Type: Complete search
 4  Algorithm:

uva 681 - Convex Hull Finding

  1  /*
  2  Problem link
  3  Type: Geometry
  4  Algorithm: Graham's Scan

uva 12086 - Potentiometers

 1  /*
 2  Problem link
 3  Type: Data structure - BIT
 4  Algorithm:

uva 12532 - Interval Product

  1  /*
  2  Problem link
  3  Type: Data structure - Binary index (Fenwick) tree
  4  Algorithm:

uva 11988 - Broken Keyboard (a.k.a. Beiju Text)

  1 /*
  2  Problem link
  3  Type: Data structure - link list
  4  Algorithm:

uva 450 - Little Black Book

  1  /*
  2  Problem link
  3  Type: Adhoc - Sorting
  4  Algorithm:

uva 410 - Station Balance

  1 /*
  2  Problem link
  3  Type: Recursion - Greedy
  4  Algorithm:

uva 10171 - Meeting Prof. Miguel...

  1  /*
  2  Problem link
  3  Type: Graph - Floyd
  4  Algorithm:

uva 572 - Oil Deposits

 1  /*
 2  Problem link
 3  Type: Graph
 4  Algorithm: DFS
 5  */

uva 11733 - Airports

 1 /*
 2  Problem link
 3  Type: Graph
 4  Algorithm:
 5      Kruskal, stop when the number of edge selected is equal to n-1 or the price of the edge
 6      equal to the cost to build an airport.
 7  */

uva 311 - Packets

  1  /*
  2  Problem link
  3  Type: Ad hoc, Greedy
  4  Algorithm:

uva 216 - Getting in Line

  1 /*
  2  Problem link
  3  Type: DP - TSP
  4  Algorithm: Brute force, back-tracking
  5  */

uva 469 - Wetlands of Florida

/*
Problem link
Type: Graph
Algorithm: BFS/DFS
*/

uva 10098 - Generating Fast

 1  /*
 2  Problem link
 3  Type: Adhoc
 4  Algorithm:
 5  */

uva 10018 - Reverse and Add

/*
 Problem link
 Type: Ad hoc
 Algorithm:
 */

CF 279C - Ladder

 1  /*
 2  Problem link
 3  Type: Binary Search
 4  Algorithm:

uva 571 - Jugs

  1  /*
  2  Problem link
  3  Type: Graph - DP
  4  Algorithm: BFS
  5  */

uva 186 - Trip Routing

  1  /*
  2  Problem link
  3  Type: Graph
  4  Algorithm: Floyd
  5  */

uva 11517 - Exact Change

/*
Problem link
Type: DP - Coin change
Algorithm:
*/

uva 10313 - Pay the Price

 1 /*
 2  Problem link
 3  Type: DP - coin change
 4  Algorithm:

Red - black tree full implementation

Red-black tree is known for an efficient data structure use in computer science. It is a type of self-balance binary search tree, it performs insertion, deletion, searching,.. in the worst running time of O(lg n). This is my red-black tree implementation in C++:

uva 10009 - All Roads Lead Where?

  1 /*
  2  Problem link
  3  Type: Graph
  4  Algorithm: BFS
  5  */

uva 11137 - Ingenuous Cubrency

 1 /*
 2  Problem link
 3  Type: DP
 4  Algorithm: Coin change
 5  */

uva 10306 - e-Coins

 1  /*
 2  Problem link
 3  Type: DP - Coins change
 4  Algorithm:
 5      First I use the function getP to search for a list of possible points with
 6       length = s from the origin and have possitive coordinates.
 7      Use the coins change algorithm (uva 166) with a few changes to find the
 8       minimum step to each point i got. Get the minimum for each point result.
 9  */

uva 10278 - Fire Station

  1 /*
  2  Problem link
  3  Type: Graph - Single source shortest path
  4  Algorithm:
  5      First run Floyd (or Dijkstra to every vertex n), for each vertex
  6      find the distance to the nearest station, get the max of those nearest station.
  7  
  8      For the vertex which is not a station, place a station there and run Dijkstra
  9      for that vertex. Recalculate the distance to the nearest station for each vertex
 10      by the distance array from the Dijkstra and update the for the "better max".
 11  */

uva 100 - The 3n + 1 problem

/*

Problem link

Type: Adhoc

Algorithm: Straight forward 

*/ 

uva 140 - Bandwidth

/*

Problem link

Type: Ad hoc

Algorithm: Complete search

*/ 

uva 1208 - Oreon

  1  /*
  2  Problem link
  3  Type: Graph
  4  Algorithm: MST
  5  */

uva 908 - Re-connecting Computer Sites

 1  /*
 2  Problem link
 3  Type: Graph
 4  Algorithm: MST
 5  */

uva 299 - Train Swapping

 1  /*
 2  Problem link
 3  Type: Ad hoc, Sorting.
 4  Algorithm: Insertion Sort.
 5  */

uva 11710 - Expensive subway

/*

Problem link

Type: Graph

Algorithm: Minimum spanning tree

uva 357 - Let Me Count The Ways

/*

Problem link

Type: DP - Coin change

*/

uva 821 - Page Hopping

 1 /*
 2  Problem link
 3  Type: Graph
 4  Algorithm:
 5      Use floyd to find all pair shortest path, sum them up, divide to the number of pair
 6      I use the map to mark for the vertex in the input.
 7  */

uva 423 - MPI Maelstrom

 1 /*
 2  Problem link
 3  Type: Graph
 4  Algorithm:
 5      Use Floyd or Dijkstra to find the shortest path from 1 to n-1 others nodes.
 6      Find the max of the shortest path from 1 to n-1 others nodes.
 7  */