Diagnostic assessment of the borg MOEA for many-objective product family design problems

• Published in: 2012 IEEE Congress on Evolutionary Computation pp. 1 - 10
• Main Authors: Hadka, D., Reed, P. M., Simpson, T. W.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2012
• Subjects: Aircraft; Algorithm design and analysis; Approximation methods; Educational institutions; Search problems; Sensitivity analysis
• ISBN: 1467315109; 9781467315104
• ISSN: 1089-778X
• DOI: 10.1109/CEC.2012.6256466

The recently introduced Borg multiobjective evolutionary algorithm (MOEA) framework features auto-adaptive search that tailors itself to effectively explore different problem spaces. A key auto-adaptive feature of the Borg MOEA is the dynamic allocation of search across a suite of recombination and mutation operators. This study explores the application of the Borg MOEA on a real-world product family design problem: the severely constrained, ten objective General Aviation Aircraft (GAA) problem. The GAA problem represents a promising benchmark problem that strongly highlights the importance of using auto-adaptive search to discover how to exploit multiple recombination strategies cooperatively. The auto-adaptive behavior of the Borg MOEA is rigorously compared against its ancestor algorithm, the ε-MOEA, by employing global sensitivity analysis across each algorithm's feasible parameter ranges. This study provides the first Sobol' sensitivity analysis to determine the individual and interactive parameter sensitivities of MOEAs on a real-world many-objective problem.