Case Studies

This section provides examples of solving optimization, mathematical, and graph problems using PyQBPP.

Math Problems

1. Pythagorean Triples (Easy)
2. Remainder Problem (Easy)
3. Square Root (Medium)
4. Greatest Common Divisor (GCD) (Easy)
5. Math Problem: Find Three Integers (Easy)
6. 3-Digit Math Problem (Easy)
7. Cubic Equation (Easy)

Graph Problems

1. Maximum Independent Set (MIS) Problem (Easy)
2. Max-Cut Problem (Easy)
3. Maximum Matching Problem (Easy)
4. Maximum Clique Problem (Easy)
5. Minimum Vertex Cover Problem (Easy)
6. Minimum Dominating Set Problem (Medium)
7. Subgraph Isomorphism Problem (Hard)
8. Minimum Set Cover Problem (Medium)
9. Minimum Maximal Matching Problem (Medium)
10. Graph Coloring Problem (Easy)
11. Graph Edge Coloring Problem (Easy)
12. Capacitated Vehicle Routing Problem (CVRP) (Hard)
13. Traveling Salesman Problem (Medium)
14. Minimum Graph Bisection Problem (Easy)

Combinatorial Optimization Problems

1. Knapsack Problem (Medium)
2. Shift Scheduling Problem (Hard)
3. LABS Problem (Medium)
4. Cutting Stock Problem (Hard)
5. Integer Linear Programming (Easy)
6. Interval Subset Sum Problem (ISSP) (Hard)

Puzzle

1. Magic Square (Hard)
2. N-Queens Problem (Medium)
3. SEND + MORE = MONEY Problem (Hard)

Satisfiability

1. Boolean Satisfiability Problem (SAT) (Easy)
2. Not-All-Equal SAT (NAE-SAT) (Easy)

Circuit Simulation

1. Adder Simulation (Medium)
2. Multiplier Simulation and Factorization (Hard)

NOTE Graph case studies include visualization code using matplotlib and networkx. Install them with: pip install matplotlib networkx