A Study on Various Methods of Sudoku Solving
- Citation:
- Nigam, Aviral, and Manish Kumar Yadav. A Study on Various Methods of Sudoku Solving. National Institute of Technology, Calicut, Report.
Abstract:
The Sudoku puzzle is most frequently a 9 X 9 grid made up of 3 X 3 sub-grids. Some cells already contain numbers. The goal is to fill in the empty cells, one number in each, so that each column, row, and sub-grids contain the numbers 1 through 9 exactly once. Each number in the solution therefore occurs only once in each of three directions. Most puzzles are ranked as to difficulty, but the rankings vary from designer to designer. Genetic Algorithms are adaptive heuristic search and an optimization algorithm premised on the mechanism of biological evolution of chromosomes. The basic concept of Genetic Algorithm is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin. Cultural Algorithms are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to the population component. In this sense, Cultural Algorithms can be seen as an extension of a conventional Genetic Algorithm. The objective of this paper is to review the concepts of Genetic Algorithm and Cultural Genetic Algorithm and finding an efficient method for solving Sudoku puzzles.
This project comprised of studying the concepts of "Genetic Algorithm & Cultural Genetic Algorithm" and fi nding an efficient method for solving Sudoku puzzles.
