- Central force optimization
- Artificial physics optimization
- Gravitational search algorithm
- Gravitational interaction optimization
- Immune gravitation inspired optimization algorithm
- Electromagnetism-like heuristic
- Charged system search
- Mass and Energy Balances Algorithm
- Momentum Balance Algorithm
- Quantum-inspired genetic algorithm
- Quantum-inspired evolutionary algorithm
- Semiphysical Quantum Mechanics
Physics-based algorithms generally fall into the realms of metaheustics and computational intelligence, although they do not fit perfectly into the existing categories of biologically inspired techniques (such as Swarm, Immune, Neuronal, and Evolution). With this in mind, they could just as easily be called nature-inspired algorithms.
Inspirational physical systems range from metallurgy, music, the interplay between culture and evolution, and complex dynamic systems such as avalanches. They are generally stochastic optimization algorithms with a mixture of local (neighborhood-based) and global search techniques.