Hybrid real-code ant colony optimisation for constrained mechanical design

Abstract

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

Keywords:

• real-code ant colony optimisation
• simplex downhill
• constrained optimisation
• hybrid algorithms
• Latin hypercube sampling

Acknowledgements

The authors are grateful for support from the Thailand Research Fund [Grant number BRG5580017].

Additional information

Notes on contributors

Nantiwat Pholdee

Nantiwat Pholdee received his BEng degree (Second Class Honors) in mechanical engineering in 2008 and his PhD degree in mechanical engineering in 2013 from Khon Kaen University, Khon Kaen, Thailand. His research interests include multidisciplinary design optimisation, evolutionary computation and finite-element analysis.

Sujin Bureerat

Sujin Bureerat received his BEng degree in mechanical engineering from Khon Kaen University, Khon Kaen, Thailand, in 1992, and his PhD degree in mechanical engineering from Manchester University, Manchester, UK, in 2001. Currently, he is an associate professor with the Department of Mechanical Engineering, Khon Kaen University. His research interests include multidisciplinary design optimisation, evolutionary computation, aeroelastic design of aircraft structures, finite-element analysis, agricultural machinery and mechanical vibration.