Development and Testing of Three Level Chaotic Slime Mould Algorithm (3L-CSMA) for Solving Complex Optimization Problems

Slime Mould Algorithm (SMA) is a highly promising meta-heuristic algorithm influenced by the food acquisition system of a Slime Mould. Chaos theory has proven its credibility in enhancing the performance of meta-heuristic optimization algorithms. In this work, the effect of incorporating three level chaos in improving the performance of SMA is studied. Ten well-known chaotic maps are integrated in initialization, exploration and exploitation stages of the original SMA, introducing ten new chaotic variants of SMA, named 3L-CSMA1 - 3L-CSMA10. These chaotic variants of SMA, are tested against twenty-two IEEE CEC benchmark functions from CEC’21 and CEC’22. To further validate the suitability of 3L-CSMAs against practical engineering problems, chaotic SMA adaptations are tested against multi-dimensional power system optimization problem Combined Heat and Power Economic Emission Dispatch (CHPEED). The simulation results revealed the significant improvement of 3L-CSMAs in finding the global optima, providing better fitness and improved solution to the complex functions compared to the original SMA and other advanced optimization algorithms.