Antarctic Icefish Optimization Algorithm
Fuente:
Zenodo
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Recurso digital |
| Pubblicazione: |
Zenodo
2026
|
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866902189948010496 |
|---|---|
| author | Zhang, Jincheng |
| author_facet | Zhang, Jincheng |
| contents | <p><span>To address issues such as premature convergence, uneven dimensional coupling, and local minima trapping in high-dimensional complex optimization problems, this paper proposes a swarm optimization algorithm based on the coupling of a non-equilibrium low-temperature dissipative structure and an information diffusion field. Inspired by the adaptation mechanism of Antarctic icefish in extreme low-temperature, high-dissolved-oxygen environments, the algorithm constructs a free energy-driven non-equilibrium evolution model, introduces a structural order parameter and a phase transition determination mechanism, designs an information oxygen diffusion field coupling term, and establishes a direction-dependent memory viscosity tensor and a curvature-tuned cooling and contraction mechanism. Instead of aiming at a single fitness decrease, the algorithm achieves swarm self-organized evolution by minimizing the free energy function. Theoretical analysis shows that this algorithm can be considered a discrete dissipative dynamic system with a stable equilibrium structure and adaptive step-size contraction characteristics. This paper systematically presents the mathematical model, update equations, dynamic interpretation, and convergence discussion</span>.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18609601 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Antarctic Icefish Optimization Algorithm Zhang, Jincheng <p><span>To address issues such as premature convergence, uneven dimensional coupling, and local minima trapping in high-dimensional complex optimization problems, this paper proposes a swarm optimization algorithm based on the coupling of a non-equilibrium low-temperature dissipative structure and an information diffusion field. Inspired by the adaptation mechanism of Antarctic icefish in extreme low-temperature, high-dissolved-oxygen environments, the algorithm constructs a free energy-driven non-equilibrium evolution model, introduces a structural order parameter and a phase transition determination mechanism, designs an information oxygen diffusion field coupling term, and establishes a direction-dependent memory viscosity tensor and a curvature-tuned cooling and contraction mechanism. Instead of aiming at a single fitness decrease, the algorithm achieves swarm self-organized evolution by minimizing the free energy function. Theoretical analysis shows that this algorithm can be considered a discrete dissipative dynamic system with a stable equilibrium structure and adaptive step-size contraction characteristics. This paper systematically presents the mathematical model, update equations, dynamic interpretation, and convergence discussion</span>.</p> |
| title | Antarctic Icefish Optimization Algorithm |
| url | https://doi.org/10.5281/zenodo.18609601 |