AFO Solving real-world problems

versión 1.3 (422 KB) por Zhe Yang
A new Nature-inspired optimization algorithm: Aptenodytes Forsteri Optimization algorithm (AFO)

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Actualizada 26 Mar 2022

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A new nature-inspired optimization algorithm: Aptenodytes Forsteri Optimization algorithm (AFO)


Yang Z, Deng L B, Wang Y, et al. Aptenodytes Forsteri Optimization: Algorithm and applications[J]. Knowledge-Based Systems, 2021, 232: 107483.


更新日志 Updating Log


Version 1.3

It is experimentally found that the gradient estimation strategy is less efficient in most cases. Here the replacement is Gaussian perturbation with a perturbation step of x_c the average distance from x


where x_new is the new individual position; Rn is a 1xN matrix of random numbers obeying normal distribution; x_r1 and x_r2 are the positions of the r1st and r2nd penguins in the population, r1 and r2 are randomly generated, and Dm is the average distance of x_c from all penguins in the population in each dimension, a 1xN matrix.

Ps:Perturbation step of x_c distance x_m is also a good choice, interested in their own experiments.



其中,x_new是新个体位置; Rn是一个1xN的随机数矩阵,服从正态分布; x_r1和x_r2是种群中第r1和第r2只企鹅的位置,r1和r2随机生成,Dm是x_c距离种群中所有企鹅在每一个维度上的平均距离,是一个1xN的矩阵。


(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) Aviation scheduling: multi-sector
(4) Flexible workshop scheduling
(5) Raster maps: robot pathfinding
(6) Logistics centre location problem: factory-centre-demand point
(7) Multi-row shop floor layout considering AVG partitioning
(8) Oil plants: UAVs for 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 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.
学校:英国曼彻斯特大学 Author:Yang Zhe
School: University of Manchester, UK %%--------------------------------------------%%




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Zhe Yang (2022). AFO Solving real-world problems (, GitHub. Recuperado .

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