Transit search: An optimization algorithm based on exoplanet exploration

In this article, a novel astrophysics-inspired meta-heuristic optimization algorithm, namely Transit Search (TS) is proposed based on a famous exoplanet exploration method. More than 3800 planets have been detected using transit technique by the database of the space telescopes. Transit is a method that has shown more potential than the second well-known successful method (radial velocity) with 915 discovered planets until 2022 March. It is difficult to detect the planets because of their small dimension in the cosmos scale. Due to the high efficiency of the transit method in astrophysics and its capabilities, it has been used to formulate an optimization technique for this research. In the transit algorithm, by studying the light received from the stars at certain intervals, the changes in luminosity are examined and if a decrease in the amount of the received light is observed, it indicates that a planet passes from the star front. In order to evaluate the capability of the proposed algorithm, 73 constrained and unconstrained problems are considered and the results have been compared with 13 wellknown optimization algorithms. This set of examples includes a wide range of types of problems including mathematical functions (28 high-dimensional and 15 low-dimensional problems), CEC functions (10 problems), constrained mathematical benchmark problems (G01-G13), as well as 7 constrained engineering problems. The results indicated that the overall average error for the proposed algorithm is the lowest amount for the benchmark problems in comparison with the other efficient algorithms