Versione 1.2 (418 KB) da Zhe Yang
A new Nature-inspired optimization algorithm: Aptenodytes Forsteri Optimization algorithm (AFO)
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Aggiornato 3 set 2021


A new nature-inspired optimization algorithm: Aptenodytes Forsteri Optimization algorithm (AFO)
(1)所有代码使用matlab2021a编写,但matlab 2021a和之前版本可能存在兼容问题,有可能出现乱码。如果乱码,使用txt打开,再将txt中的代码复制到.m文件当中

There are two folders, one for the code of AFO experiments on the standard test set and one for the application of AFO to some practical problems
In addition to the four industrial design problems mentioned in the thesis, there are other problems in the collection, which are listed below
(1) The four industrial design problems with constraints mentioned in the paper
(2) Optimising the weights and thresholds of neural networks
(3) Airline scheduling - multiple sectors
(4) Flexible shop floor scheduling
(5) Raster maps - robot pathfinding
(6) Logistics centre location problem: factory-centre-demand point
(7) Multi-row shop floor scheduling - considering AVG partitioning
(8) Oil plant - UAV path planning
(9) Power system bus optimization based on tide calculation
(10) Optimization study of cold chain distribution logistics vehicle scheduling for a dairy company
(11) Plasma processing trajectory planning for 6R-oriented industrial robots
(12) TSP problem and its variant problems

(1) All code is written using matlab 2021a, but there may be compatibility problems between matlab 2021a and previous versions, and garbled codes may appear. If the code is garbled, use txt to open it and copy the code from txt to .m file
(2) Improved algorithms for AFO will be added later, as well as more application examples. The lab has participated in and completed hundreds of applications based on swarm intelligence, including power systems, workshop scheduling, logistics and distribution, site layout, UAV path planning, robot path planning, complex network optimisation, resource scheduling, optimisation of various machine learning algorithms and other directions. The lab will continue to select classic cases to add to this code collection, so please stay tuned. If you need code for a particular direction, please leave a message or contact us by email.
(3) Our lab has published a large number of high-level improvement algorithms, which will be added to this code collection one after another, so please pay attention to them.
%%--------------------------------------------%% Copy right
You are free to use all the code in this code base, but please give credit and cite the relevant references.
Author:Yang Zhe
E-mail: 454170989@qq.com
School: University of Manchester, UK, Harbin Institute of Technology,China

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Zhe Yang (2024). A-new-Nature-inspired-optimization-algorithm-AFO (https://github.com/TwilightArchonYz/A-new-Nature-inspired-optimization-algorithm-AFO/releases/tag/1.2), GitHub. Recuperato .

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See release notes for this release on GitHub: https://github.com/TwilightArchonYz/A-new-Nature-inspired-optimization-algorithm-AFO/releases/tag/1.2

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