Header menu link for other important links
Solving Sudoku Using Neighbourhood-Based Mutation Approach of Genetic Algorithm
S. Jana, A. Dey, A.K. Maji,
Published in Springer Science and Business Media Deutschland GmbH
Volume: 241
Pages: 153 - 167
Sudoku, an NP-complete-based mathematical puzzle, has different levels of difficulty. There are several techniques to solve this interesting mathematical conundrum. Our effort anticipated a neighbourhood-based mutation approach of the Genetic Algorithm to solve Sudoku instances. In this paper, the fixed two-point crossover along with neighbourhood-based mutation is implemented. For mutation, a neighbour checking concept is incorporated to get rid of unwanted swaps. The newness of our proposed method is that considering less population Sudoku instances can be solved with a greater success rate for easy, medium, and hard difficulty level puzzles. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalLecture Notes in Networks and Systems
PublisherSpringer Science and Business Media Deutschland GmbH