Abstract
This paper introduces a hybrid shape optimization method (M-HYBRID) for multiple objectives (MO) using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) in combination with a meshless computational fluid dynamics solver. It uses the reference point based approach to reach the required optimum. This method was found to converge faster than MO optimizer based on GA alone. The constraint on the handling large number of parameters with MO optimiser based on ACO is overcome in M-HYBRID. This hybrid optimizer is good contender when a global optimum is the target. © 2010 Springer-Verlag.
Author supplied keywords
Cite
CITATION STYLE
Sashi Kumar, G. N., Mahendra, A. K., Sanyal, A., & Gouthaman, G. (2010). A hybrid method for multi-objective shape optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6457 LNCS, pp. 563–567). https://doi.org/10.1007/978-3-642-17298-4_61
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
