The paper introduces the Arithmetic Optimization Algorithm (AOA), a novel meta-heuristic optimization method inspired by the distribution behavior of arithmetic operators (Multiplication, Division, Subtraction, and Addition). AOA is designed to solve optimization problems in various search spaces and is mathematically modeled to balance exploration and exploitation. The performance of AOA is evaluated on 29 benchmark functions and several real-world engineering design problems. Experimental results show that AOA outperforms eleven other well-known optimization algorithms in terms of solution quality and computational efficiency. The AOA's source code is publicly available, and the paper discusses its potential future research directions, including the exploration of other arithmetic and evolutionary operators, hybridization with other stochastic components, and application in various disciplines.The paper introduces the Arithmetic Optimization Algorithm (AOA), a novel meta-heuristic optimization method inspired by the distribution behavior of arithmetic operators (Multiplication, Division, Subtraction, and Addition). AOA is designed to solve optimization problems in various search spaces and is mathematically modeled to balance exploration and exploitation. The performance of AOA is evaluated on 29 benchmark functions and several real-world engineering design problems. Experimental results show that AOA outperforms eleven other well-known optimization algorithms in terms of solution quality and computational efficiency. The AOA's source code is publicly available, and the paper discusses its potential future research directions, including the exploration of other arithmetic and evolutionary operators, hybridization with other stochastic components, and application in various disciplines.