Hybrid Sine Cosine Algorithm for Solving Engineering Optimization Problems

Engineering design optimization problems are difficult to solve because the objective function is often complex, with a mix of continuous and discrete variables various constraints. Our research presents novel hybrid algorithm that integrates benefits sine cosine (SCA) artificial bee colony (ABC) address engineering problems. The SCA recently developed metaheuristic many advantages, such as good search ability reasonable execution time, but it may suffer from premature convergence. enhanced equation proposed avoid this drawback reach preferable balance between exploitation exploration abilities. In method, named HSCA, improved strategy ABC two distinct equations run alternately during working on same population. multiple can provide proper diversity in population so both algorithms complement each other create beneficial cooperation their merger. Certain feasibility rules incorporated HSCA steer towards feasible areas space. applied fifteen demanding investigate its performance. presented experimental results indicate method performs better than basic ABC. accomplishes pretty competitive compared recent state-of-the-art methods.