An Improved Shuffled Frog Leaping Algorithm for Solving Controlled Optimization Problems of Water Bath Stretching Slot

Abstract: Basic shuffled frog leaping algorithm (SFLA) easily traps into local minimum and has slower convergence. To overcome these shortcomings, this paper proposes an improved SFLA, which combines the cell communication mechanism. By modifying the update formula, the improved algorithm can maintain the population diversity and enhance the convergence velocity and precision. The comparison with several kinds of optimization algorithms are made for four benchmark test functions. Experimental results show that the improved SFLA is effective and robust. Finally, the improved algorithm is applied to the optimization of the water bath stretching slot control system in carbon fiber production, which further demonstrates the effectiveness of the improved SFLA.