Metaheuristic algorithms have garnered a lot of attention in the optimization field. Humans have been using metaheuristic algorithms to solve problems for last decade. Using concepts from natural selection, evolution, and problem-solving techniques, the application of these techniques to combinatorial optimization issues has quickly expanded as a field of study. In this paper, a novel meta-heuristic optimization method is proposed, called “Bermuda Triangle Optimizer (BTO)”. The underlying concepts of the farmer one is inspired by the force of attraction of Bermuda, which many aircraft and ships are mysteriously disappeared in this area. The area of attractive force has a form of triangle roughly bounded by Florida, Bermuda, and Puerto Rico in which attracts any object to the center of triangle. Based on this theory, this point can be considered as the best solution (optimal value). BTO is tested in solving test bed suites of “Congress on Evolutionary Computation (CEC 2017)”. The BTO is compared against well-known physical based optimization algorithms, which are “Chernobyl Disaster Optimizer (CDO)”, and “Gravitational Search Algorithm (GSA)”. The outcomes of this study prove the performance of BTO in which can be considered as viable alternative.