@misc{Ławrynowicz_Anna_A_2010,
 author={Ławrynowicz, Anna},
 year={2010},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2010; Nr 104, s. 148-165},
 language={eng},
 abstract={In this paper, the author proposed a novel intelligent method to support an integration of operating decision making in new structures of business. This approach focuses on interactions between the various firms within a cluster at operations management level in order to improve manufacturing processes. The author proposed a novel intelligent method for a collective scheduling in an industrial cluster. For this purpose, the genetic algorithm proposed by the author in previous work by Ławrynowicz [2008] is developed. The new genetic algorithm for the collective scheduling is based on operation codes, where each chromosome is a set of 4-positions genes. The proposed method is verification on some experiments. The analysis presented in the article shows that the new genetic algorithm proposed by the author can be used to improve a detailed scheduling in the cluster. Moreover, the proposed genetic algorithm may aid planners in transport orders planning. It can be applied in a dynamic setting when rescheduling is initiated by unexpected changes.},
 title={A Novel Intelligent Method to Support Operations Management in Clusters},
 type={artykuł},
 keywords={cluster, operation, management, genetic algorithm},
}