The 16 Queen is the problem of placing 16 chess queens on an 16×16 chessboard so that no two queens attack each other.

Naive Algorithm: Generates all possible configurations of queens on board and print a configuration that satisfies the given constraints.

Genetic Algorithm: Generates different configurations of queens on board based on cross-over and mutation rate and print a configuration that statisfies the given constraints.

Naive Algorithm vs Genetic Algorithm - Naive algorithm searches through the entire search space whereas Genetic algorithm effectively searches through the search space based on the fitness of the solutions.

• Compiler - onlinegdb.com (online C++ compiler)
• Text Editor - Notepad++

• 16-Queen Problem.pptx - A Powerpoint presentation about the code and its theory

• main.c - Source code

A genetic algorithm is a search heuristic that is inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection where the fitest solutions are selected for cross-over in order to produce new solutions of the next generation.

1. Parent generation
2. Fitness calculation
3. Tournament selection is used to select the best parent for cross-over process
4. Cross-over operation (PMX)
5. Mutation operation (Activation of this operation depends on the mutation rate)
6. Cross-over and mutation operation together generates the next generation solutions
7. Check if any solution has fitness value 0 (max fitness), if false repeat from step 2
8. Prints the optimal solution