Icefield Mouse Optimization Algorithm

Swarm intelligence optimization algorithms are a class of metaheuristic optimization methods inspired by the collective behavior of animals in nature, and are widely used in continuous, discrete, and constrained optimization problems. This paper proposes a novel swarm intelligence optimization algorithm—Icefield Mouse Optimization (IMO)—inspired by the foraging, risk avoidance, and cooperative behavior of icefield mice in polar environments. This algorithm achieves a balance between global exploration and local exploitation through dynamic individual energy allocation, multi-strategy search, environmentally aware risk avoidance, and adaptive group cooperation mechanisms. IMO demonstrates good global search capability and convergence stability for complex multimodal functions and high-dimensional optimization problems. This paper details the algorithm modeling, iterative process, mathematical formulas, and mechanism analysis, and discusses its application and expansion potential.