Transit Search Optimization Algorithm (2022): MATLAB Codes

The codes of a novel astrophysics-inspired meta-heuristic optimization algorithm, namely Transit Search (TS)

Welcome to the world of Transit Search (TS), a cutting-edge optimization algorithm that draws inspiration from the remarkable method of exoplanet detection known as transit. The TS presents a novel astrophysics-inspired meta-heuristic approach to solving complex scientific problems. With more than 3800 planets detected using the transit technique by space telescopes, this algorithm harnesses the power of transit exploration and adapts it to the realm of optimization.

The benefits of employing the TS algorithm in scientific research and problem-solving are manifold. Firstly, optimization lies at the heart of many scientific disciplines, from industrial internet of things to wireless networks, shape optimization of electric machines to vulnerability assessment of structures subjected to seismic activity. By leveraging TS, researchers can unlock new frontiers in their respective fields and achieve optimal solutions efficiently.

Unlike classical methods, which may guarantee optimal responses but struggle with complex and large-scale problems, meta-heuristic algorithms like TS excel in tackling such challenges. These algorithms may not guarantee finding the absolute best solution, but they excel in approximating optimal and acceptable answers within a reasonable timeframe. TS strikes a delicate balance between exploration and exploitation, employing innovative strategies inspired by the natural phenomena observed in exoplanet detection.