Adaptive switching heuristic based evolutionary algorithm

The ASHEA offers a revolutionary meta-heuristic approach for resolving challenging scientific problems.

Welcome to the space of Adaptive switching heuristic based evolutionary algorithm (ASHEA), a state-of-the-art optimization algorithm inspired by the Differential Evolution (DE), Cuckoo Search Algorithm (CSA) and Firefly Algorithm (FA). The ASHEA offers a revolutionary meta-heuristic approach for resolving challenging scientific problems belonging to engineering, industrial application, CEC competitions and more.

The program codes are easy for new researcher to implement. ASHEA takes advantage of the adaptive switching between global search and local search to find better solutions faster than other algorithms. It handles complex, high-dimensional problems smoothly and uses an archive pool to remember previous best steps along with incorporation of parallel processing and random samplings. Researchers can effectively find the best solutions and open up new avenues in their fields by utilizing ASHEA.

ASHEA is applied to solve complex optimization problems across diverse real-world fields, including chemical process engineering and mechanical engineering. It is also extensively used in electrical engineering for power systems and electronics, in applied domains, and in optimizing livestock feed rations also.