In this paper, a novel metaheuristic approach called The Three-point Optimization Algorithm (TPOA) is proposed. TPOA is inspired by the principle of three point positioning. Three point positioning is a geometric based positioning method that determines the position of a target by measuring the distance between the target point and a known point. This method has a wide range of applications in multiple fields, including geological surveying, satellite navigation systems, and WeChat positioning. TPOAs performance is demonstrated by benchmarking with 10 well-known test functions (including unimodal, multimodal, fixed-dimension multimodal, and composite functions). Moreover, TPOAs results are verified by comparison to 5 other metaheuristics. In this study, the experimental results for the above 6 methods on the 10 testing functions in terms of the Mean (mean value), Std (standard deviation), the Best(the best value), the Worst(the worst value), and Burden(cost time), and it suggest that TPOAs results are competitive and, in many instances, outperform the aforementioned well-known metaheuristics.