Hybridizing the electromagnetism-like algorithm with descent search for solving engineering design problems

Abstract

In this paper, we present a new stochastic hybrid technique for constrained global optimization. It is a combination of the electromagnetism-like (EM) mechanism with a random local search, which is a derivative-free procedure with high ability of producing a descent direction. Since the original EM algorithm is specifically designed for solving bound constrained problems, the approach herein adopted for handling the inequality constraints of the problem relies on selective conditions that impose a sufficient reduction either in the constraints violation or in the objective function value, when comparing two points at a time. The hybrid EM method is tested on a set of benchmark engineering design problems and the numerical results demonstrate the effectiveness of the proposed approach. A comparison with results from other stochastic methods is also included.

Keywords:

• hybrid method
• electromagnetism-like mechanism
• descent search
• sufficient reduction
• engineering design problems

2000 AMS Subject Classifications :

• 90C15
• 90C56
• 90C30

Acknowledgements

The authors would like to thank the two anonymous referees for their constructive comments and suggestions.

Notes

We used a value of 32 for the maximum stopping time constraint, taken from the Pareto front in 23.

We used a value of 0.04 for the maximum joint displacement constraint, taken from the Pareto front 23.

, as shown in 16.