An Empirical Analysis of Genetic Algorithm with Different Mutation and Crossover Operators for Solving Sudoku

Author:

Srivatsa D.,Teja T. P. V. Krishna,Prathyusha Ilam,Jeyakumar G.ORCID

Publisher

Springer International Publishing

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comparative Performance Analysis of Genetic Algorithm Variants on Solving 0/1 Knapsack Problem;2023 IEEE World Conference on Applied Intelligence and Computing (AIC);2023-07-29

2. A Genetic Algorithm Framework to Solve Two-Dimensional Maze Problem;Lecture Notes in Electrical Engineering;2022

3. Solving Sudoku Using Neighbourhood-Based Mutation Approach of Genetic Algorithm;Lecture Notes in Networks and Systems;2021-11-03

4. A novel hybrid genetic algorithm-based firefly mating algorithm for solving Sudoku;Innovations in Systems and Software Engineering;2021-05-24

5. Optimization of Excitation and Commutation Angles of Switched Reluctance Motor Using Micro-Genetic Algorithm;Cognitive Informatics and Soft Computing;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3