Optimization algorithms play a crucial role in engineering, computer science, and artificial intelligence. In recent years, heuristic algorithms have garnered significant attention due to their flexibility and global search capabilities. However, most traditional algorithms rely on existing natural inspirations or mathematical mechanisms, lacking innovative approaches that integrate complex physiological systems. This paper proposes a novel optimization algorithm based on obstetric and perinatal health physiological mechanisms—the Placental-Maternal Dynamic Optimization (PMDO) algorithm. The algorithm simulates a three-layered dynamic regulatory mechanism involving the mother, fetus, and placenta, mapping maternal resources, placental transfer coefficients, and fetal state to the optimization search process, achieving an adaptive balance between global exploration and local development. The paper delves into the algorithm's principles, mathematical mechanisms, parameter interpretation, and potential applications, constructing a complete pure-text mathematical formula system that demonstrates the application value of perinatal health physiological characteristics in optimization algorithms.