Improving the performance of water cycle algorithm using augmented Lagrangian method. (June 2019) - Bahreininejad, Ardeshir
Highlights: Constraint handling using augmented Lagrangian method. Water cycle algorithm (WCA) is inspired by water cycle process and explosion of landmines. Incorporation of augmented Lagrangian method in WCA called WCA-ALM. WCA-ALM offers significant convergence efficiency. Abstract: In this paper, a study was carried out to investigate the application and impact of the Augmented Lagrange Method (ALM) on the recently proposed Water Cycle Algorithm (WCA). The WCA-ALM was compared with the original WCA for constrained optimization of some engineering benchmark problems. The performance of quadratic penalty method was also investigated in this research. The approach transforms a constrained problem into an unconstrained problem by imposing penalty on the objective function. The comparison results show significant performance in convergence as well as solution quality in some cases. Furthermore, a simulation was also carried out to examine how the method handles constraints regarding feasible and infeasible solutions. The results show ALM efficiently handles the constraints for the WCA algorithm resulting in improved convergence and/or solution quality.