[FEAT]: Proposal for Dandelion Optimizer (DO)

[halilakbas11]

Description

Hello, I would like to contribute to Mealpy with a bio-inspired optimization algorithm called the Dandelion Optimizer (DO).

About the Algorithm:
The Dandelion Optimizer (DO) is a nature-inspired, plant-based metaheuristic optimization algorithm inspired by the long-distance dispersal behavior of dandelion seeds under different wind and weather conditions. The algorithm models the life cycle of dandelion seeds as they rise, descend, and finally land in suitable locations to grow, which naturally translates into an effective balance between exploration and exploitation.

DO is designed for continuous optimization problems and does not rely on gradient information. Instead, it uses stochastic movements driven by environmental factors such as wind intensity and weather, allowing the algorithm to escape local optima and explore the search space efficiently.

The algorithm consists of three main stages:

Rising stage (exploration):
Dandelion seeds are lifted by wind and weather conditions. Depending on environmental factors, seeds either explore the global search space using stochastic spiral movements or perform local exploration.

Descending stage (guided exploration):
Seeds descend steadily using Brownian motion while being guided by the average position of the population, helping the search move toward promising regions.

Landing stage (exploitation):
Seeds land near the best solution found so far and use Lévy flight–based movements to refine solutions and improve convergence accuracy while avoiding premature convergence.

Reference & Original paper:
Dandelion Optimizer: A Nature-Inspired Metaheuristic Algorithm for Engineering Applications
Engineering Applications of Artificial Intelligence, Vol. 114, 2022.
DOI: 10.1016/j.engappai.2022.105075
https://www.mathworks.com/matlabcentral/fileexchange/114680-dandelion-optimizer
https://www.sciencedirect.com/science/article/pii/S0952197622002305

Motivation for Mealpy:
I believe the Dandelion Optimizer fits well within Mealpy because:

-It is a bio-inspired, plant-based, population-based metaheuristic optimization algorithm.
-It has a clear mathematical formulation with distinct exploration and exploitation phases.
-It has been validated on CEC benchmark functions and real-world engineering optimization problems.

Contribution Plan:

Implement the Dandelion Optimizer in Python using NumPy, following Mealpy’s base optimizer architecture and coding conventions.

Add clear and concise comments explaining the mathematical formulation and biological inspiration.

Provide a usage example and benchmark tests (e.g., using the opfunu library with CEC 2017 functions).

Ensure full consistency with existing optimizers in the Mealpy repository.

I would really appreciate your feedback on whether this contribution aligns with Mealpy’s goals.
Thank you very much for your time and for maintaining such a valuable optimization library.

Additional Information

No response