Dashboard
Signal #142638NEUTRAL

Ecological Cycle Optimizer: A novel nature-inspired metaheuristic algorithm for non-convex global optimization

96

arXiv:2508.20458v2 Announce Type: replace Abstract: This article proposes the Ecological Cycle Optimizer (ECO), a novel metaheuristic algorithm inspired by energy flow and material cycling within ecosystems. ECO draws an analogy between the dynamic process of solving optimization problems and ecological cycling. Unique update strategies are designed for the producer, consumer and decomposer, aiming to enhance the balance between exploration and exploitation processes. Through these strategies, ECO is able to approach the global optimum, simulating the evolution of an ecological system toward its optimal state of stability and balance. Moreover, a parameter sensitivity analysis is conducted on 23 classic optimization functions to determine a suitable default configuration for ECO. Furthermore, 30 competitive metaheuristic algorithms are selected to form an algorithm pool, and comprehensive experiments are conducted on the IEEE CEC-2014 and CEC-2017 test suites. Among these, five top-per...

arXiv Neural/NEabout 2 hours ago
Read Full Article

Explore with AI-Powered Tools

View All Signals

Explore more AI intelligence

Want to discover more AI signals like this?

Explore Steek
Ecological Cycle Optimizer: A novel nature-inspired metaheuristic algorithm for non-convex global optimization | Steek AI Signal | Steek