Production scheduling problem and solver improvement via integration of the grey wolf optimizer into the augmented Lagrangian relaxation method-Reference-Cited by-同舟云学术

Production scheduling problem and solver improvement via integration of the grey wolf optimizer into the augmented Lagrangian relaxation method

Published:2020-11-09 Issue:12 Volume:2 Page:
ISSN:2523-3963
Container-title:SN Applied Sciences
language:en
Short-container-title:SN Appl. Sci.

Author:

Tolouei Kamyar,Moosavi Ehsan

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Physics and Astronomy,General Engineering,General Environmental Science,General Materials Science,General Chemical Engineering

Link

http://link.springer.com/content/pdf/10.1007/s42452-020-03758-z.pdf

Reference61 articles.

1. Turgut MS, Turgut OE (2020) Differential evolution based global best algorithm: an efficient optimizer for solving constrained and unconstrained optimization problems. SN Appl Sci 2:600

2. Goldberg DE (1989) Genetic algorithms in search. Optim Mach Learn

3. Wei Y, Qiqiang L (2004) Survey on particle swarm optimization algorithm. Eng Sci 5(5):87–94

4. Dorigo M, Birattari M (2010) Ant colony optimization. Springer, Berlin

5. Banzhaf W, Nordin P, Keller RE, Francone, FD (1998) Genetic programming: an introduction. 1,. Morgan Kaufmann, San Francisco

Cited by 2 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. Enumeration optimization of open pit production scheduling based on mobile capacity search domain;Scientific Reports;2023-01-03

2. Modified grey wolf optimizer-based support vector regression for ship maneuvering identification with full-scale trial;Journal of Marine Science and Technology;2021-11-02