/**The first stage: practice classic common algorithms, each of the following algorithms will be marked ten to twenty times for me, and at the same time simplify the code by myself,
Because it is too commonly used, so you don't have to think about it when you practice writing, you can type it out within 10-15 minutes, or even turn off the monitor to type out the program.
1. Shortest path (Floyd, Dijstra, BellmanFord)
2. Minimum spanning tree (write a prim first, kruscal uses a union check set, it is not easy to write)
3. Large numbers (high precision) addition, subtraction, multiplication and division
4. Binary search. (The code can be within five lines)
5. Cross product, judge the intersection of line segments, and then write a convex hull.
6. BFS, DFS, and proficient in hash tables (familiar, flexible, and simple in code)
7. Mathematically, there are: tossing and dividing (within two lines), intersection of line segments, area formula of polygons.
8. Calling the system's qsort, there are many skills, master it slowly.
9. Conversion between arbitrary bases
*/
Stage 2: Practice more complex, but also more commonly used algorithms.
Such as:
1. Bipartite graph matching (Hungary), minimum path coverage
2. Network flow, minimum cost flow.
3. Line segment tree.
4. And check the set.
5. Familiar with the typical dynamic programming: LCS, longest increasing substring, triangulation, memoized dp
6. Game algorithm. Game tree, binary method, etc.
7. The largest group, the largest independent set.
8. Determine that the point is within the polygon.
9. Differentially constrained systems.
10. Bidirectional breadth search, A* algorithm, minimum dissipation priority.
relevant knowledge
Graph Theory
path problem
0/1 edge weight shortest path
BFS
Non-negative edge weight shortest path (Dijkstra)
Features that can be solved with Dijkstra
Negative edge weight shortest path
Bellman-Ford
Bellman-Ford's Yen-Optimization
Differential Constraint System
Floyd
generalized path problem
transitive closure
Minimax Distance / Minimax Distance
Euler Path / Tour
loop-and-loop algorithm
Euler Path/Tour for Hybrid Graphs
Hamilton Path / Tour
Hamilton Path / Tour construction for special graphs
spanning tree problem
minimum spanning tree
kth smallest spanning tree
optimal ratio spanning tree
0/1 Score Planning
Degree-constrained spanning tree
connectivity issues
Powerful DFS algorithm
undirected graph connectivity
cut point
cut edge
two connected branches
Directed graph connectivity
Strongly connected branch
2-SAT
minimum point basis
Directed Acyclic Graph
topological sort
The relationship between directed acyclic graph and dynamic programming
Bipartite graph matching problem
The idea of conversion between general graph problem and bipartite graph problem
Maximum match
Minimum path coverage for directed graphs
Minimal Coverage of 0/1 Matrix
perfect match
best match
stable marriage
network flow problem
Simple Characteristics of Network Flow Models and Relation to Linear Programming
Maximum flow min-cut theorem
maximum flow problem
Maximum flow problem with upper and lower bounds
circulating flow
Min-Fee Max-Flow / Max-Fee Max-Flow
Properties and Judgments of Chord Diagrams
Combinatorial Mathematics
Common ideas for solving combinatorial math problems
Approach
recursive/dynamic programming
probability problem
Polya's Theorem
Computational Geometry / Analytical Geometry
The Heart of Computational Geometry: Cross Product / Area
The Workhorse of Analytic Geometry: Complex Numbers
basic form
point
&n
...