Research Area:  Metaheuristic Computing

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.

Keywords:  
Water Cycle Algorithm
Lagrangian method
objective function
convergence

Author(s) Name:  Ardeshir Bahreininejad

Publisher name:  Elsevier

DOI:  10.1016/j.advengsoft.2019.03.008

Volume Information:  Volume 132

Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S0965997818310639