Draft:Greedy Man Optimization Algorithm

Draft article not currently submitted for review.

This is a draft Articles for creation (AfC) submission. It is not currently pending review. While there are no deadlines, abandoned drafts may be deleted after six months. To edit the draft click on the "Edit" tab at the top of the window.

To be accepted, a draft should:

Show the subject qualifies for a Wikipedia article by using multiple sources that meet four criteria. The sources should be (1) reliable (2) secondary (3) independent of the subject (4) talk about the subject in some depth. For some topics, there are alternative criteria.
Be written from a neutral point of view
Respect copyright and do not plagiarize. Do not copy-paste.

It is strongly discouraged to write about yourself, your business or employer. If you do so, you must declare it.

Where to get help

If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews.
If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed.

How to improve a draft

Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia.
Help:Wikitext – how to use the markup
Help:Referencing for beginners – how to include references
Wikipedia:Article development – how to develop your article
Wikipedia:Writing better articles – how to improve your article
Wikipedia:Verifiability – make sure your article includes reliable third-party sources

You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article.

Improving your odds of a speedy review

To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags.

Add tags to your draft

Editor resources

Easy tools: Citation bot (help) | Advanced: Fix bare URLs

Last edited by 87.200.87.208 (talk | contribs) 14 days ago. (Update)

Submit the draft for review!

Greedy Man Optimization Algorithm (GMOA) is a nature-inspired metaheuristic optimization algorithm developed by Hamed Nozari in 2024. The algorithm is inspired by the behavioral interaction between a "greedy man" and "resource parasites," simulating the competitive nature of resource consumption and resistance. It is designed to efficiently balance exploration and exploitation in solving complex optimization problems.

Inspiration and Mechanism

The core concept of GMOA revolves around modeling a greedy individual's attempt to monopolize resources while being confronted by parasites that develop resistance. This metaphor is implemented mathematically to create a dynamic balance between intensification and diversification. GMOA introduces competitive operators, resistance adaptation, and resource allocation dynamics to improve convergence.

Mathematical Model

The algorithm defines greedy agents and parasite populations with update rules for position, resistance, and dominance. The population evolves iteratively using stochastic and deterministic components inspired by natural competition. The mathematical framework mimics:

Resource greediness (exploration pressure)
Parasite resistance (diversification)
Stability through adaptive penalty functions

Applications

GMOA has been applied in various optimization contexts, including engineering design, feature selection, scheduling, and multi-objective problems. Its competitive structure makes it suitable for problems with rugged landscapes and deceptive local optima.

Implementation

A MATLAB implementation of GMOA is publicly available on MATLAB Central File Exchange.^[1]

References

^ "Greedy Man Optimization Algorithm (GMOA)". MATLAB Central. Retrieved 31 March 2025.

Nozari, Hamed (2025). "Greedy Man Optimization Algorithm: A Novel Approach to Problem Solving with Resistant Parasites". Journal of Industrial and Systems Engineering.
"Greedy Man Optimization Algorithm (GMOA)". ResearchGate. Retrieved 31 March 2025.
"Greedy Man Optimization Algorithm (GMOA)". Academia.edu. Retrieved 31 March 2025.

Inspiration and Mechanism

Mathematical Model

Applications

Implementation

References

See also