The paper presents a nature-inspired derivative-free global optimization method, namely the fish shoal algorithm (FSA), for solving engineering optimization problems with costly objective functions. The method is intended for unconstrained single-objective maximization and is based on a simplified social model of a fish shoal in search for food. Derivative-free global optimization approaches are usually preferred to derivative-based local approaches, when objectives are noisy, derivatives are unknown and the existence of multiple local optima cannot be excluded, as often encountered in simulation-based design (SBD) optimization. When global techniques are used with CPU- time expensive solvers, the optimization process is computationally expensive and its effectiveness and efficiency remain an algorithmic and technological challenge.
A fish shoal algorithm for global derivative-free simulation-based ship design optimization
Matteo Diez;Andrea Serani;
2014
Abstract
The paper presents a nature-inspired derivative-free global optimization method, namely the fish shoal algorithm (FSA), for solving engineering optimization problems with costly objective functions. The method is intended for unconstrained single-objective maximization and is based on a simplified social model of a fish shoal in search for food. Derivative-free global optimization approaches are usually preferred to derivative-based local approaches, when objectives are noisy, derivatives are unknown and the existence of multiple local optima cannot be excluded, as often encountered in simulation-based design (SBD) optimization. When global techniques are used with CPU- time expensive solvers, the optimization process is computationally expensive and its effectiveness and efficiency remain an algorithmic and technological challenge.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.