The goal of the paper is to show how the Grid and its infrastructure can provide a valid support for reducing time and costs related to the execution of a generic optimization process in industrial world. An optimization model, the micro-GA algorithm, based on Genetic Algorithm theory, has been thought as the combination of a central generic optimization manager and several specific modules, characterized by the nature of the optimization problem, to be executed on a set of distributed and heterogeneous resources. A case study for the optimization of Diesel Engine performance, in terms of emission levels and fuel consumption, is presented as example of real applicability of the method. Finally, a prototypal implementation of described algorithm in a Grid Environment is provided.
Industrial Problem Optimization in a Grid Environment
ALOISIO, Giovanni;BLASI E;EPICOCO, Italo;MOCAVERO S.
2006-01-01
Abstract
The goal of the paper is to show how the Grid and its infrastructure can provide a valid support for reducing time and costs related to the execution of a generic optimization process in industrial world. An optimization model, the micro-GA algorithm, based on Genetic Algorithm theory, has been thought as the combination of a central generic optimization manager and several specific modules, characterized by the nature of the optimization problem, to be executed on a set of distributed and heterogeneous resources. A case study for the optimization of Diesel Engine performance, in terms of emission levels and fuel consumption, is presented as example of real applicability of the method. Finally, a prototypal implementation of described algorithm in a Grid Environment is provided.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
