I want a list of Meta-heuristics algorithms that consider the velocity vector to update the solution's position in the next iteration like: PSO, GSA, DA (Dragonfly) ...
Salem,
i have found these ones:
- Cockroach-Based Optimization
-Gravitational Search Algorithm
-Artificial Physics Optimization
-Kinetic Gas Molecule Optimization
-Wind Driven Optimization
all these metaheuristics and others can be found in the book entitled :
"Search and Optimization
by Metaheuristics
Techniques and Algorithms Inspired by Nature"
You can see this link : http://www.springer.com/us/book/9783319411910
Best regards.
The original algorithm introducing this concept to metaheuristics research was PSO. Roughly speaking, you can take any animal species presenting a swarm behavior and turn it into an algorithm inspired by it using particle velocities, which many researchers do.
As Mr. Mohamed said, Particle Swarm Optimization is one of those algorithms you are looking for. In every iteration of this algorithm, velocity of individuals, here known as particles, will be adjusted according to the social behavior of the whole swarm.
In addition to the algorithms that are previously mentioned by the users, I would mention to the Differential Evolution algorithm, which is successfully (and widely) applied on different calsses of optimization problems.
Best reragrds,
Based on your consideration that any one parameter of the Metahueristic algorithms, i.e. linked with iteration and it is linked with its position updation then it is updated upto max iterations.
@Josimar Chire
I am thinking to compare between different algorithms after studying a common behavior between all of them.
Swarm-based Algorithms is the most popular such as:
PSO : Particle Swarm Optimization
WOA : Whale Optimization Algorithm
BA : Bat Algorithm
SSA: Slap Swarm Algorithm
GOA: Grasshopper Optimization algorith
Since the introduction of PSO, many other swarm intelligence approaches have been introduced. As this concept has becoming challenging, the number of algorithms is growing up each year. I can cite for instance the water wave optimization, which has not been yet mentioned here. Also, several new hybridizations have been proposed. Some of them have assembled for instance particle swarm optimization and gravitational search algorithm or other algorithms.
In recent years, many new evolutionary algorithms have been proposed, and people are more willing to use these new algorithms to solve the optimization problem. In fact, the performance of these new evolutionary algorithms is no better than classical evolutionary algorithms, such as genetic algorithm, particle swarm optimization, differential evolution, artificial fish swarm algorithm, ant colony optimization and artificial bee colony.
PSO : Particle Swarm Optimization
WOA : Whale Optimization Algorithm
BA : Bat Algorithm
SSA: Slap Swarm Algorithm
DA: Dragonfly Algorithm
GOA: Grasshopper Optimization algorithm
GSA: Gravitational Search Algorithm
WDO: Wind Driven Optimization
SOA: Spider Optimization algorithm
IWD: Intelligent Water Drops algorithm
CSO: Cockroach-Based Optimization
APO: Artificial Physics Optimization
KGMO: Kinetic Gas Molecule Optimization
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