# A Brief Overview of Physics-inspired Metaheuristic Optimization Techniques

arXiv: https://arxiv.org/abs/2201.12810 · HTML: https://mlsanity.com/paper/2201.12810/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 30 Jan 2022.

## Builds on (most cited first, 1 of 1)

- [An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation](https://mlsanity.com/paper/1405.5066/) (2014)

## Abstract (arXiv)

Metaheuristic algorithms are methods devised to efficiently solve computationally challenging optimization problems. Researchers have taken inspiration from various natural and physical processes alike to formulate meta-heuristics that have successfully provided near-optimal or optimal solutions to several engineering tasks. This chapter focuses on meta-heuristic algorithms modelled upon non-linear physical phenomena having a concrete optimization paradigm, having shown formidable exploration and exploitation abilities for such optimization problems. Specifically, this chapter focuses on several popular physics-based metaheuristics as well as describing the underlying unique physical processes associated with each algorithm.