Coastal Ecosystem Inspired Optimization

Fuente: Zenodo
Enregistré dans:
Détails bibliographiques
Auteur principal: Zhang, Jincheng
Format: Recurso digital
Publié: Zenodo 2025
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866902127474900992
author Zhang, Jincheng
author_facet Zhang, Jincheng
contents <p><span>Coastal ecosystems, located in the transition zone between land and sea, possess complex physical environments, diverse biomes, and dynamic ecological processes. This study proposes a Coastal Ecosystem Inspired Optimization (CEOI) algorithm that seamlessly integrates global search with local exploitation by simulating ecological features such as tides, dune sedimentation, salt marsh buffering, mangrove stabilization, and energy flows in food webs. The algorithm not only retains elite solutions but also enhances the swarm's search capabilities through dynamic boundary perturbations, random jumps, and adaptive elimination mechanisms. This paper details the algorithm's principles, swarm structure, update mechanism, and mathematical formulation, providing new insights into natural ecologically inspired optimization methods.</span></p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17070487
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Coastal Ecosystem Inspired Optimization
Zhang, Jincheng
<p><span>Coastal ecosystems, located in the transition zone between land and sea, possess complex physical environments, diverse biomes, and dynamic ecological processes. This study proposes a Coastal Ecosystem Inspired Optimization (CEOI) algorithm that seamlessly integrates global search with local exploitation by simulating ecological features such as tides, dune sedimentation, salt marsh buffering, mangrove stabilization, and energy flows in food webs. The algorithm not only retains elite solutions but also enhances the swarm's search capabilities through dynamic boundary perturbations, random jumps, and adaptive elimination mechanisms. This paper details the algorithm's principles, swarm structure, update mechanism, and mathematical formulation, providing new insights into natural ecologically inspired optimization methods.</span></p>
title Coastal Ecosystem Inspired Optimization
url https://doi.org/10.5281/zenodo.17070487