Parameter selection in synchronous and asynchronous deterministic particle swarm optimization for ship hydrodynamics problems
| Autor: | Umberto Iemma, Matteo Diez, Giovanni Fasano, Andrea Serani, Emilio F. Campana, Cecilia Leotardi |
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| Přispěvatelé: | Serani, Andrea, Leotardi, Cecilia, Iemma, Umberto, Campana, Emilio F., Fasano, Giovanni, Diez, Matteo |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Meta-optimization ship hydrodynamics optimization Computer science Initialization 02 engineering and technology 020901 industrial engineering & automation Derivative-free optimization 0202 electrical engineering electronic engineering information engineering Multi-swarm optimization Metaheuristic Global optimization derivative-free optimization particle swarm optimization global optimization Particle swarm optimization Swarm behaviour Solver Simulation-based design Simulation based design Derivative free optimization Global optimization Particle swarm optimization Ship hydrodynamics optimization Simulation-based design derivative-free optimization global optimization particle swarm optimization ship hydrodynamics optimization Test functions for optimization 020201 artificial intelligence & image processing Settore MAT/09 - Ricerca Operativa Heuristics Software |
| Zdroj: | Applied soft computing 49 (2016): 313–334. doi:10.1016/j.asoc.2016.08.028 info:cnr-pdr/source/autori:Serani, Andrea; Leotardi, Cecilia; Iemma, Umberto; Campana, Emilio F.; Fasano, Giovanni; Diez, Matteo/titolo:Parameter selection in synchronous and asynchronous deterministic particle swarm optimization for ship hydrodynamics problems/doi:10.1016%2Fj.asoc.2016.08.028/rivista:Applied soft computing (Print)/anno:2016/pagina_da:313/pagina_a:334/intervallo_pagine:313–334/volume:49 |
| DOI: | 10.1016/j.asoc.2016.08.028 |
| Popis: | Graphical abstractDisplay Omitted HighlightsParametric study of deterministic PSO setting under limited computational resources.Comparison of synchronous and asynchronous implementations.Identification of most significant parameter based on more than 40k optimizations.Identification of most promising and robust setup for simulation-based problems.Hydrodynamic hull-form optimization of a high speed catamaran. Deterministic optimization algorithms are very attractive when the objective function is computationally expensive and therefore the statistical analysis of the optimization outcomes becomes too expensive. Among deterministic methods, deterministic particle swarm optimization (DPSO) has several attractive characteristics such as the simplicity of the heuristics, the ease of implementation, and its often fairly remarkable effectiveness. The performances of DPSO depend on four main setting parameters: the number of swarm particles, their initialization, the set of coefficients defining the swarm behavior, and (for box-constrained optimization) the method to handle the box constraints. Here, a parametric study of DPSO is presented, with application to simulation-based design in ship hydrodynamics. The objective is the identification of the most promising setup for both synchronous and asynchronous implementations of DPSO. The analysis is performed under the assumption of limited computational resources and large computational burden of the objective function evaluation. The analysis is conducted using 100 analytical test functions (with dimensionality from two to fifty) and three performance criteria, varying the swarm size, initialization, coefficients, and the method for the box constraints, resulting in more than 40,000 optimizations. The most promising setup is applied to the hull-form optimization of a high speed catamaran, for resistance reduction in calm water and at fixed speed, using a potential-flow solver. |
| Databáze: | OpenAIRE |
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