A crucial problem in nowadays industrial automation applications regards the (sub)optimal setting of parameters (both physical and logical) that influence system behavior; in this regard, the verification phase of functional constraints satisfaction plays a fundamental role. To deal with this problems, the designer should rely on powerful simulation tools able to enlighten how different settings influence the designed application. The idea behind this work is to use an operational research engine based on metaheuristic algorithms to drive the simulation model in order to find optimal settings for the modeled system minimizing given cost objectives.
Genetic algorithm for the optimization of a packing line / C.Bonivento; A.Paoli; M.Sartini; E.Morganti. - ELETTRONICO. - 5:(2007), pp. 1-6. (Intervento presentato al convegno 5th Workshop on Advanced Control and Diagnosis http://www.lag.ensieg.inpg.fr/acd-2007/ tenutosi a Grenoble, France nel November 15-16, 2007).
Genetic algorithm for the optimization of a packing line
BONIVENTO, CLAUDIO;PAOLI, ANDREA;SARTINI, MATTEO;
2007
Abstract
A crucial problem in nowadays industrial automation applications regards the (sub)optimal setting of parameters (both physical and logical) that influence system behavior; in this regard, the verification phase of functional constraints satisfaction plays a fundamental role. To deal with this problems, the designer should rely on powerful simulation tools able to enlighten how different settings influence the designed application. The idea behind this work is to use an operational research engine based on metaheuristic algorithms to drive the simulation model in order to find optimal settings for the modeled system minimizing given cost objectives.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
