Let me make a statement first: The article is directly copied and pasted from the push in my personal official account, so friends who are interested in intelligent optimization algorithms can follow my personal official account: < a i=1>Heuristic algorithm discussion. I will share different intelligent optimization algorithms in the public account from time to time, classic ones, or new intelligent optimization algorithms proposed in recent years, with MATLAB codes attached.
“Today I’m sharing one of my ‘black technologies’, that is, every time the code is run, there will be a sound prompting me. It’s very simple to say, just add a small piece of code~”
Most articles on intelligent optimization algorithms and numerical experiments use different algorithms to run test sets. A test set contains multiple Benchmark functions, and the algorithm will be run multiple times on each function. Then, we can't keep staring at MATLAB to see when it finishes running, and then proceed to the next step.
At this time, it would be nice if there was a prompt sound to remind us. Here, I will share with you some of the sound programs that come with MATLAB. Add it directly to the end of the main function. After the entire program is finished running, the computer will issue a beep to inform you that the program is finished~
Below are some prompt sounds that I collected and organized. You can directly copy and paste them to run.
1. Birdsong
load chirpsound(y,Fs)
2. The sound of a gong
load gongsound(y,Fs)
3. Hallelujah
load handelsound(y,Fs)
4. Laughter
load laughtersound(y,Fs)
5. snapping sound
load splatsound(y,Fs)
6. The sound of the train
load trainsound(y,Fs)
You can copy it directly into the command line window of MATLAB to try the effect~
As for running the algorithm, we all know that if the number of independent runs is set to 50, sometimes it takes several hours for an algorithm to complete a test set. At this time, the prompt sound command can be placed in the main program main.m at last. In this way, once the code is finished running, you will be reminded in time, and then you can proceed to the next step.
While the code is running, you can wear the headphones and do other things without having to open MATLAB from time to time to check whether the program has finished running. Because after the program is finished running, you can hear the prompt sound from the headphones ~
Also, I have written some code recently and the code listing has been updated. Added MATLAB codes for several algorithm applications:Wireless Sensor Network (WSN) node coverage optimization (2D environment), Wireless Sensor Network (WSN) node coverage optimization (3D environment), zero idle ( no-idle flow shop scheduling problem (NIFSP), zero-wait flow shop scheduling problem (NWFSP), blocking flow shop scheduling problem (BFSP), distributed replacement flow shop scheduling problem (DPFSP)< /span>.
This week is quite busy and I don’t have enough time to take care of the public account. These applications may not be pushed one by one. You can directly download the list and look for it in the list. For each application, some classic algorithms or algorithms that have been highly recognized in recent years are selected for solution.
Having said that, I will share with you the algorithms that I personally approve of in the past ten years (2013-2023):
Gray Wolf Optimization (GWO), Whale Optimization (WOA), Harris Hawk Optimization (HHO), Sparrow Search Algorithm (SSA), Marine Predator Algorithm (MPA), African Vulture Optimization Algorithm (AVOA), Chrysanthemum Mantis optimization (DBO), Star Crow optimization algorithm (NOA).
These are the algorithms that I personally recognize. Because I have tested their performance, they are not "soft persimmons". They not only perform well on the test set, but also have excellent competitiveness in many practical problems. The latest one here is NOA, which was just proposed. If you don’t understand, you can check the previous push:Star Crow Optimization Algorithm (NOA) (including MATLAB code)
I personally tested a variety of test sets and practical problems, and the performance of NOA is not inferior to that of DBO, or even better!
For more views on these algorithms, we can discuss them in the algorithm exchange group! Algorithm communication group: 912369858. Welcome everyone to join the group to communicate, thank you!
The above is today’s simple sharing~
You can download the code list through the link below, find the required algorithm code in it, and then go to the corresponding link to obtain it. The list will be updated simultaneously, and once new code is available, it can be found in the list. Some of the codes in the list are obtained from open source. Available for free download at any time.
Connection:https://pan.baidu.com/s/1SFDMplrL7tiqGZlrpOSGYg
Receipt:8023