1. Hybrid global/local derivative-free multi-objective optimization via deterministic particle swarm with local linesearch
- Author
-
Andrea Serani, Umberto Iemma, Emilio F. Campana, Giampaolo Liuzzi, Francesco Rinaldi, Stefano Lucidi, Riccardo Pellegrini, Matteo Diez, Nicosia G.,Giuffrida G.,Pardalos P.,Umeton R., Pellegrini, Riccardo, Serani, Andrea, Liuzzi, Giampaolo, Rinaldi, Francesco, Lucidi, Stefano, Campana, Emilio F., Iemma, Umberto, and Diez, Matteo
- Subjects
Mathematical optimization ,Computer science ,0211 other engineering and technologies ,02 engineering and technology ,Derivative ,Multi-objective optimization ,Theoretical Computer Science ,Deterministic optimization ,Derivative-free optimization ,0202 electrical engineering, electronic engineering, information engineering ,Particle swarm optimization Linesearch method ,Local search (optimization) ,Linesearch method ,Derivative-free optimization Deterministic optimization ,021103 operations research ,business.industry ,Global local ,Particle swarm optimization ,Computer Science (all) ,Hybrid global/local optimization ,Hybrid algorithm ,Hybrid global/local optimization Multi-objective optimization ,020201 artificial intelligence & image processing ,business - Abstract
A multi-objective deterministic hybrid algorithm (MODHA) is introduced for efficient simulation-based design optimization. The global exploration capability of multi-objective deterministic particle swarm optimization (MODPSO) is combined with the local search accuracy of a derivative-free multi-objective (DFMO) line search method. Six MODHA formulations are discussed, based on two MODPSO formulations and three DFMO activation criteria. Forty-five analytical test problems are solved, with two/three objectives and one to twelve variables. The performance is evaluated by two multi-objective metrics. The most promising formulations are finally applied to the hull-form optimization of a high-speed catamaran in realistic ocean conditions and compared to MODPSO and DFMO, showing promising results.
- Published
- 2018