Eight-colored Thrush Optimization Algorithm

Swarm intelligence optimization algorithms, which simulate the collective behavior of organisms in nature to solve complex optimization problems, have been widely applied in engineering, economics, and computer science. This paper proposes a novel swarm intelligence optimization algorithm—the Eight-colored Thrush Optimization Algorithm (ETOA). This algorithm simulates the foraging, social interaction, and migration behavior of pittas, and designs a multi-stage search strategy, a hierarchical migration mechanism, dynamic energy regulation, and a multimodal information sharing mechanism. ETOA achieves high-precision solutions to complex multimodal optimization problems by means of three stages: global exploration, local refinement, and migration optimization, while ensuring population diversity and search efficiency. This paper also provides a detailed theoretical analysis of the algorithm, including convergence, diversity preservation, and scalability analysis, proving its broad applicability and good performance in continuous, discrete, and constrained optimization problems.