see compact genetic algorithm. It can give better performance compared to ordinary genetic algorithm

Social Spider Algorithm is a newly developed optimization technique.

Between latest it is Integration of Variables Method. In it frame was developed by me a group of concrete heuristi cs. Really in it frame it is possible to create a very wide set of different algorithms matching to different concret problems. From my researchgate profile you can dowload by example "The Integtration of Variables method: a generalization of Genetic", "Conciliación óptima de la distribución de piezas de configuración irregular y su corte "Optimal conciliation between distribution on the foil of irregular configuration pieces and it cutting", "Analisys and Synthesis of Engineering Systems",  "Un algoritmo del Método de Integración de Variables para la solución del problema Máximo Clique Ponderado"  and others deveted devoloving and using this metheod,

Jose Arzola-Ruiz

Dear Arvind Kumar,

Some of recently developed algorithms are linked for you.

http://www.sciencedirect.com/science/article/pii/S1568494615006742

http://link.springer.com/article/10.1007/s00158-015-1396-8

http://www.sciencedirect.com/science/article/pii/S0957417416300677

Hi Arvind,

Not only have I proposed a new metaheurisitc, I have also cited Sorensen's explanation for why there are too many of them.

What makes Leaders and Followers a worthwhile addition to multitudes of "new" metaheuristics?

1 - It is based on how solutions are compared, not how they are created.  Most metaheuristics (e.g PSO, DE, ACO, GA, EDA, etc) focus on how solutions are created.  Only a few (e.g. Simulated Annealing and Tabu Search) focus on how solutions are compared.  Unlike Simulated Annealing and Tabu Search, Leaders and Followers is a population-based method.

2 - Leaders and Followers is extremely simple -- arguably simpler than PSO, DE, ACO, EDA, etc.  Many new metaheuristics are more complicated than existing metaheuristics.  In general, any addition to a metaheuristic can improve it's performance (witness the thousands of papers produced each year).  Getting improved performance with a more complicated algorithm is no big deal.  Getting improved performance with a simpler algorithm?  Now that gets interesting!

3 - Leaders and Followers is compared against well established versions of PSO and DE on a full benchmark (CEC2013) of problems.  Many introductions of metaheuristics (e.g. PSO) don't demonstrate their performance against legitimate competition.

Hope that helps.

Cheers,

Stephen

Article Metaheuristics -- the metaphor exposed

Conference Paper Leaders and Followers – A New Metaheuristic to Avoid the Bia...

Another recently developed metaheuristic is Minimum Population Search (MPS). This metaheuristic is specifically designed to optimize real-valued, multi-modal and high dimensional functions.

Conference Paper Minimum Population Search – Lessons from building a heuristi...

Conference Paper Extending Minimum Population Search towards Large Scale Glob...

Conference Paper A Minimum Population Search Hybrid for Large Scale Global Optimization

you can check the following site:

ALIMirjalili.com/Projects.html

Salp Swarm Algorithm

Symbiotic Organisms Search

All the answers are great

Galactic Swarm Optimization

Coyote Optimization Algorithm

Article Galactic Swarm Optimization: A New Global Optimization Metah...

https://ieeexplore.ieee.org/document/8477769

Please find our recent work on simulating the optimization algorithm's behavior using the deep learning models:

Preprint From feature selection to continuous optimization

2017: Spotted hyena optimizerArticle Spotted Hyena Optimizer: A Novel Bio-inspired based Metaheur...

2018 : Coyote Optimization Algorithm

2018: Mouth Brooding Fish algorithmArticle Tackling global optimization problems with a novel algorithm...

2018: Seagull optimization algorithm

Article Seagull optimization algorithm: Theory and its applications ...

2018:Yellow Saddle Goatfish behavior

Article A novel bio-inspired optimization model based on Yellow Sadd...

2019: Equilibrium optimizer

Article Equilibrium optimizer: A novel optimization algorithm

2019:Manta ray foraging optimization

https://doi.org/10.1016/j.engappai.2019.103300

2019: A Novel Bat Algorithm

doi:10.3390/math7020135

2019: The Sailfish Optimizer

Article The Sailfish Optimizer: A novel nature-inspired metaheuristi...

2019: social ski driver algorithm

2019: Squirrel search algorithm

https://doi.org/10.1016/j.swevo.2018.02.013

* EO (Equilibrium Optimizer) 2019

* SOA (Seagull Optimization Algorithm) 2019

* STOA (Sooty Tern Optimization Algorithm) 2019

* MRFO (Manta Ray Foraging Optimization)

You can find a huge list at the Evolutionary Computation Bestiary.

https://github.com/fcampelo/EC-Bestiary

You might also be amused by a paper which shows the superiority of modern paranormal distribution techniques.

A Spectral Approach to Ghost Detection

http://oneweirdkerneltrick.com/spectral.pdf

Article Historical survey on metaheuristics algorithms

Article Battle royale optimization algorithm

Matlab code: https://www.taymaz.dev/battle-royale-optimization-algorithm/

useful link:

https://techheuristic.blogspot.com/2020/06/list-of-metaheuristic-algorithms-from.html

Mayfly optimization algorithm

https://www.sciencedirect.com/science/article/abs/pii/S036083522030293X

Also, take a look here:

https://en.wikipedia.org/wiki/List_of_metaphor-based_metaheuristics

And here:

https://github.com/fcampelo/EC-Bestiary

I hope that helped

The shuffled shepherd optimization algorithm

Article Shuffled shepherd optimization method: a new Meta-heuristic algorithm

HHO: Harris'-Hawks Optimization (2019)

Spotted hyena optimizer Article Spotted Hyena Optimizer: A Novel Bio-inspired based Metaheur...

You will find a complete list of Meta-heuristic algorithms here :

Article Gaining-sharing knowledge based algorithm for solving optimi...

Plasma generation optimization: a new physically-based metaheuristic algorithm for solving constrained optimization problems, Engineering Computations (2020).

Article Plasma generation optimization: a new physically-based metah...

Chaos Game Optimization

More info can be found here:

Article Chaos Game Optimization: a novel metaheuristic algorithm

Search and Rescue Optimization Algorithm (SAR) 2019

Article A New Optimization Algorithm Based on Search and Rescue Operations

Article Search and Rescue optimization algorithm: a new optimization...

"Sea Lion Optimization Algorithm" is one of current-state-of-the-art meta heuristic algorithms . More info can be found here:

N. K. T. El-Omari, "Sea Lion Optimization Algorithm for Solving the Maximum Flow Problem", International Journal of Computer Science and Network Security (IJCSNS), e-ISSN: 1738-7906, DOI: 10.22937/IJCSNS.2020.20.08.5, 20(8):30-68, 2020.

Or simply refer to the same paper at the following link:

https://www.researchgate.net/publication/344324283_Sea_Lion_Optimization_Algorithm_for_Solving_the_Maximum_Flow_Problem

Water Strider Algorithm (WSA) :

Article Water strider algorithm: A new metaheuristic and applications

Thermal Exchange Optimization (TEO):

Article A novel meta-heuristic optimization algorithm: Thermal excha...

Sunflower optimization (SFO)

Article Tuning metaheuristic algorithms using mixture design: Applic...

Article An efficient two-step damage identification method using sun...

Article A sunflower optimization (SFO) algorithm applied to damage i...

Lichtenberg Algorithm (LA)

Article Lichtenberg optimization algorithm applied to crack tip iden...

A POWERFUL LICHTENBERG OPTIMIZATION ALGORITHM: A DAMAGE IDENTIFICATION CASE STUDY. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2020 (In press)

You can find the source codes in Matlab/Scilab language:

https://www.mathworks.com/matlabcentral/fileexchange/77825-lichtenberg-optimization-algorithm-la

https://atoms.scilab.org/toolboxes/sunflower/1.0

https://www.mathworks.com/matlabcentral/fileexchange/69076-sunflower-optimization-sfo-algorithm

1- Multi-tracker Optimization Algorithm: A General Algorithm for Solving Engineering Optimization Problems

Article Multi-tracker Optimization Algorithm: A General Algorithm fo...

Data MTOA - Matlab Source Code

2- Adaptive multi-tracker optimization algorithm for global optimization problems: emphasis on applications in chemical engineering

Article Adaptive multi-tracker optimization algorithm for global opt...

Cellular automata based hybrid PSO and GWO algorithm. Article Cellular Automata-Based Multi-Objective Hybrid Grey Wolf Opt...

Marine Predators Algorithm (MPA)

Article Marine Predators Algorithm: A Nature-inspired Metaheuristic

lightning search algorithm (LSA)

Article Lightning Search Algorithm

Billiards-inspired optimization algorithm; a new meta-heuristic method

Stochastic paint optimizer (SPO)by Prof. Ali Kaveh , Siamak Talat Ahari, Nima Khodadadi

Dear Arvind Kumar,

The comprehensive history of previously metaheuristic optimization algorithms from the beginning period up to the latest strategies, particularly between 1975 to 2019 years, have been collected and reported in the introduction section of the annexed paper:

"Article Interactive autodidactic school: A new metaheuristic optimiz...

In this regard, take a glance at Table 1 of this research paper could be constructive for your research insight.

Hope it would be fruitful for you.

Kind regards,

MJ

Matlab code available for Billiards-inspired optimization algorithm; a new meta-heuristic method

Dear Arvind Kumar,

PSO based group oriented CSA (PGCSA) algorithm is a new optimization technique.

Please find our recent work which elaborates the advantages of machine learning including the transfer learning and ensemble learning for the numerical optimization tasks.

Dear Nima Khodadadi :

Why should I use the Stochastic paint optimizer (SPO)?!

The mathematical programming is the best optimization tool with many years of strong theoretical background. Also, it is demonstrated that it can solve complex optimization problems in the scale of one million design variable, efficiently. Also, the methods are so reliable! Besides, there is mathematical proof for the existence of the solution and the globality of the optimum.

While, metaheuristics will all fail in expensive objective functions with high numbers of design variables. Also, each single run gives different solution. So you must average the designs! This is exactly shows that the algorithm is completely unreliable! Besides, it has no theoretical background and cannot be claimed as a scientific procedure. It is called a pseudo-science! In addition, it needs more computational cost and inefficient in solving real world problems.

Looking for the term “novel metaheuristic” is only the waste of time. They all have similar concept and only it is the change of the names. What about the “novel tired panda algorithm”!! You can change many of these names and publish many papers, but they would all be useless! I had some experiences based on the metaheuristics (even some of them are under review!), but I have moved to mathematical programming and no longer work in this way.

Many supervisors are looking nothing more than citation and impact factor! They are not developing real science!

Golden Eagle Optimizer by my co-authors and I.

Article Golden Eagle Optimizer: A nature-inspired metaheuristic algorithm

Please have a look in the following discussion. It really helps you:

https://www.researchgate.net/post/Metaheuristics_and_the_Emperors_new_clothes-why_do_I_care_and_worry

I will recommend the Teaching Learning-based Optimization (TLBO) for you.

You can see in my profile the Lichtenberg Algorithm (LA). A New and powerfull metaheuristic based in population qnd trajectory.

Arithmetic optimization algorithm AOA

Archimedes optimization algorithm AOA

Chameleon Swarm Algorithm: A Bio-inspired Optimizer for Solving Engineering Design Problems

Arithmetic optimization algorithm AOA

Arithmetic optimization algorithm

Article The Arithmetic Optimization Algorithm

Equilibrium optimization

Tunicate swarm optimization

Chimp optimization algorithm

Seagull optimization algorithm

Archimedes optimization algorithm

Marine predator algorithm

Manta ray foraging optimizer

Sooty optimization algorithm

Gaining-sharing knowledge-based optimization algorithm was developed in 2020. It is based on the concept of acquiring and sharing knowledge during the human life span.

You can check this algorithm by

Mohamed, A.W., Hadi, A.A. & Mohamed, A.K. Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm. Int. J. Mach. Learn. & Cyber. 11, 1501–1529 (2020). https://doi.org/10.1007/s13042-019-01053-x

Moreover, binary versions of this algorithm are also developed.

Plant Propagation Algorithm. Never mind the metaphor, it has a great paradigm.

It was invented I think in 2011, but we've recently discovered a lot of stuff about this, such as insensitivity to parameters (very good property!) and super fast convergence through parameter control.

Emperor penguin colony, and its two modifications MEPC1 and MEPC2

Here is the DOI for one of the papers

Article Two-Modified Emperor Penguins Colony Optimization Algorithms

Chimp Optimization Algorithm

Slim mould Algorithm

Marine predator algorithm

are three novel with available source code

Article Chimp Optimization Algorithm

Multilayer Ant Colony Optimization (MLACO):

https://www.sciencedirect.com/science/article/abs/pii/S0167739X20329812

I'd highly recommend these novel algorithms from among the latest available so far:

(1) Jellyfish Optimizer (2021): Article A novel metaheuristic optimizer inspired by behavior of jell...

(2) Political Optimizer (2020): Article Political Optimizer: A novel socio-inspired meta-heuristic f...

(3) Heap-based Optimizer (2020): Article Heap-based optimizer inspired by corporate rank hierarchy fo...

(4) Manta ray foraging Optimizer (2020): Article Manta ray foraging optimization: An effective bio-inspired o...

Harris Hawks Optimization (HHO)

http://evo-ml.com/hho/

Arithmetic Optimization Algorithm (AOA)

Aquila Optimizer (AO)

You can try our hybrid optimizer: CPSOGSA (Constriction Coefficient based Particle Swarm Optimization and Gravitational Search Algorithm) for solving real-world problems (Rather and Bala, 2019).

New algorithms:

ECA* https://doi.org/10.1007/s00521-020-05649-1

LPB https://doi.org/10.1016/j.eij.2020.08.003

DSO https://doi.org/10.1016/j.jcde.2019.04.004

FDO https://doi.org/10.1109/ACCESS.2019.2907012

Modified and Hybridized algorithms:

KMGWO https://doi.org/10.1108/WJE-10-2020-0527

WOAGWO https://doi.org/10.1007/s00521-020-04823-9

WOA-BAT https://doi.org/10.1155/2019/8718571

SFGA https://doi.org/10.1016/j.jpdc.2020.05.002

IFDO 10.1109/ACCESS.2020.2968064

MGWO https://doi.org/10.1371/journal.pone.0213237

Very good question Thank you!

Bald eagle search

Lichtenberg Algorithm

Hunger games search

Battle royale optimization algorithm

Tunicate Swarm Algorithm:

I apologise

Metaheuristics are an impressive area of research with extremely important improvements in the solution of intractable optimization problems.

The following articles could be helpful

Article A survey on new generation metaheuristic algorithms

You can find an improved GWO published by ESWA in 2021 and its full source code here:

Article An improved grey wolf optimizer for solving engineering problems

I recommend you to check also the MTDE algorithm implemented by a multi-trial vector approach (MTV) which is a new and effective mechanism to improve other metaheuristic algorithms as well. The MTDE and its full source code are available here:

Article MTDE: An effective multi-trial vector-based differential evo...

You can also check the CCSA algorithm implemented by a Conscious Neighborhood-based approach which is an effective mechanism to improve other metaheuristic algorithms as well. The CCSA and its full source code are available here:

Article CCSA: Conscious Neighborhood-based Crow Search Algorithm for...

Many metaheuristics can be fit into the two main categories of Swarm Intelligence or Evolutionary Computation. A new distinct category is based on Exploration only-Exploitation only. A first example is EZ-opt:

Conference Paper The EZopt Optimisation Framework

It is worth noting that his method uses a similar definition and measurement of Exploration as Article A novel direct measure of exploration and exploitation based...

Md. Abdur Razzak Choudhury Dude you misunderstood the question. The question is "Whats are the latest meta-heuristic algorithms proposed in last years". Not tell me what do you think about Metaheuristics

I am aware of a recently proposed algorithm entitled "Battle Royale Optimization"

I think Kenneth Sörensen just published some kind of overview paper on trends in the field. Haven't read it yet. But I will do, he usually writes pretty good (if somewhat mercilessly sometimes).

Henry gas solubility optimization: A novel physics-based algorithm

Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems

Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems

Child Drawing Development Optimization Algorithm (CDDO)

Article Child Drawing Development Optimization Algorithm Based on Ch...

I ask for recent metaheuristics, that can solve efficiently graph theory problems such Steiner tree problem.

GWO, WOA, SCA, MFO, HHO, AOA, CGO etc...

Archimedes optimization algorithm and Harris hawks optimization

Kindly refer to this:

https://www.researchgate.net/publication/353403100_A_Novel_Hybrid_Metaheuristic_Based_on_Augmented_Grey_Wolf_Optimizer_and_Cuckoo_Search_for_Global_Optimization

S. Sharma, R. Kapoor and S. Dhiman, "A Novel Hybrid Metaheuristic Based on Augmented Grey Wolf Optimizer and Cuckoo Search for Global Optimization,"2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC), 2021, pp. 376-381, doi: 10.1109/ICSCCC51823.2021.9478142.

Kindly refer to this:

Jia, H., Peng, X., Lang, C., Remora Optimization Algorithm, Expert Systems with

Applications (2021), doi: https://doi.org/10.1016/j.eswa.2021.115665

We share the source codes of all MHS algorithms we have developed. Thus, we contribute to science and researchers to make new developments. Below you can find links to source codes of powerful and modern MHS algorithms published in top quality journals in the last year.

dFDB-MRFO ( Improved Manta Ray Foraging Optimizer with dFDB

https://se.mathworks.com/matlabcentral/fileexchange/96113-dfdb-mrfo-a-powerful-meta-heuristic-optimization-algorithm

FDB-AGDE (An improved version Adaptive Guided Differential Evolution)

https://se.mathworks.com/matlabcentral/fileexchange/90601-fdb-agde

FDB-SDO (An improved version of Supply-Demand Optimizer)

https://www.mathworks.com/matlabcentral/fileexchange/84560-fdb-sdo-an-improved-version-of-supply-demand-optimizer

LRFDB-COA (An improved version of Coyote Optimization Algorithm)

Levy flight and FDB-based coyote optimization algorithm for global optimization https://www.mathworks.com/matlabcentral/fileexchange/87864-lrfdb-coa

FDB-SFS (An improved version of Stochastic Fractal Search Algorithm)

https://www.mathworks.com/matlabcentral/fileexchange/84405-fdb-sfs

You can find the QANA: Quantum-based avian navigation optimizer algorithm and its FULL SOURCE CODES in the following links.Article QANA: Quantum-based avian navigation optimizer algorithm

Code Full Source codes QANA-Quantum-based avian navigation optimi...

Papers on the following metaheuristic algorithms were published between 2020 and 2021:

African vultures optimization algorithm (AVOA)

Aquila Optimizer (AO)

Archimedes optimization algorithm (AOA)

Red fox optimization algorithm (RFO)

Artificial Gorilla Troops Optimizer (GTO)

Smart Flower Optimization Algorithm (SFOA)

Battle royale optimization algorithm (BRO)

Horse herd optimization algorithm (HOA)

Black Widow Optimization Algorithm (BWO)

A knee point-driven multi-objective artificial flora optimization algorithm (kpMOAF)

Red deer algorithm (RDA)

Slime mould algorithm (SMA)

Equilibrium optimizer (EO)

Marine Predators Algorithm (MPA)

Arithmetic Optimization Algorithm (AOA)

Artificial gorilla troops optimizer

There are many metaheuristics techniques available and introduced frequently nowadays. Some of the latest techniques are:

Binary Emperor penguins optimizer

Black Widow optimization

Slime mould algorithm etc...

Hybridizing existing techniques is sometimes much beneficial for a certain types of optimization problems. You can proceed with that too...

I would like to recommend another latest metaheuristic algorithm, "African Vultures Optimization Algorithm: A New Nature-Inspired Metaheuristic Algorithm for Global Optimization Problems".

Article African Vultures Optimization Algorithm: A New Nature-Inspir...

There are many metaheuristics techniques. Pls refer to Article Advanced arithmetic optimization algorithm for solving mecha...

you can find some new ones in the literature reviewed

I've been working with metropolis coupled simulated annealers recently.

In addition there are SAGA (simulated annealing genetic algorithms) and quantumXXXX type heuristic algorithms.

Colony predator algorithm

Reptile Search Algorithm

HGSO

LFD

AOA

HBA

I would like to invite you to have a look on the following links.

SSO: https://www.mathworks.com/matlabcentral/fileexchange/92150-sperm-swarm-optimization-sso

HSSOGSA: https://www.mathworks.com/matlabcentral/fileexchange/92130-hssogsa?s_tid=srchtitle

MOSFP: https://github.com/sh7adeh1990/MOSFP

Reptile search algorithm...proposed recently may provide good results for versatile applications

Dear Nidhal, a similar metaheuristic algorithm: "Lion Optimization Algorithm (LOA)" is also present in literature.

Yazdani, M., & Jolai, F. (2016). Lion optimization algorithm (LOA): a nature-inspired metaheuristic algorithm. Journal of computational design and engineering, 3(1), 24-36.

Asthana, M., Gupta, K. D., & Kumar, A. (2020). Test Suite Optimization Using Lion Search Algorithm. In Ambient Communications and Computer Systems (pp. 77-90). Springer, Singapore.

URL: https://link.springer.com/chapter/10.1007/978-981-15-1518-7_7