Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm-Reference-Cited by-同舟云学术

Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm

Published:2019-12-18 Issue:7 Volume:11 Page:1501-1529
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Mohamed Ali Wagdy^ORCID,Hadi Anas A.,Mohamed Ali Khater^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s13042-019-01053-x.pdf

Reference142 articles.

1. Talbi E-G (2009) Metaheuristics : from design to implementation. Wiley, New York

2. Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comput Oper Res 13(5):533–549

3. Blum C, Roli A (2003) Metaheuristics in combinatorial optimization. ACM Comput Surv 35(3):268–308

4. Fogel LJ, Owens AJ, Walsh MJ (1966) Artificial intelligence through simulated evolution. Wiley

5. Rechenberg I (1994) Evolutionsstrategie: optimierung technischer systeme nach prinzipien der biologischen evolution. Frommann-holzbog, Stuttgart, 1973

Cited by 327 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. A joint optimization method for multi-UAV deployment and task scheduling in mobile edge computing with large-scale mobile users;Expert Systems with Applications;2024-12

2. GSK-LocS: Towards a more effective generalisation in population-based neural network training;Alexandria Engineering Journal;2024-12

3. Alpha evolution: An efficient evolutionary algorithm with evolution path adaptation and matrix generation;Engineering Applications of Artificial Intelligence;2024-11

4. Enhancing population diversity based gaining-sharing knowledge based algorithm for global optimization and engineering design problems;Expert Systems with Applications;2024-10

5. The Differentiated Creative Search (DCS): Leveraging differentiated knowledge-acquisition and creative realism to address complex optimization problems;Expert Systems with Applications;2024-10