The N-Queens problem is a classic puzzle that involves placing N chess queens on an N×N chessboard, such that no two queens threaten each other. In other words, no two queens should be able to attack each other directly, either horizontally, vertically, or diagonally. The problem gets its name from the chess queen's ability to move horizontally, vertically, and diagonally on the chessboard.
The N-Queens problem is often used as an example in computer science and algorithm design due to its combinatorial nature and the challenge it presents. It has applications in various fields, such as chessboard layout design, optimization, and constraint satisfaction.
A genetic algorithm (GA) is a search and optimization technique inspired by the process of natural selection and genetics. It is a type of evolutionary algorithm that mimics the principles of genetics and evolution to solve complex problems.
The origin of genetic algorithms can be traced back to the work of John Holland in the 1960s and his book "Adaptation in Natural and Artificial Systems" published in 1975. Holland, along with his colleagues and students, developed the fundamental concepts and principles of genetic algorithms.
The basic idea behind genetic algorithms is to simulate the process of natural selection, where individuals with favorable traits are more likely to survive and reproduce, passing their genetic information to the next generation. In the context of a genetic algorithm, an individual represents a potential solution to a problem, and its characteristics are encoded in a chromosome or a set of parameters.