A Novel Process to Improve the Performance of Metaheuristic Algorithms

Metaheuristic algorithms occupy the randomisation since there is no guarantee, they always provide reasonable solutions. The algorithms only can confirm global solutions to optimisation problems after a fair amount of computations. It means that a series of computations for comparison is inevitable. Thus, the world still beholds introductions of more advanced algorithms with much more excellent performance. This paper introduces a novel technique to increase the performance of the metaheuristic algorithms for optimisation problems. It is called push-process, which is a straightforward and powerful alternative for improving metaheuristic algorithms. In this paper, two well-known metaheuristic algorithms (e.g. particle swarm optimisation—PSO and bat algorithm—BA) are executed to apply the push-process. In this study, several numerical benchmarks are utilised to validate the effectiveness of the proposed technique. All numerical tests in this research are programmed by MATLAB software.