Measure characterization of a complex system logistics

Andres Velasquez Contreras, Johann Trujillo Diaz, Carlos Franco Franco, Holman Bolivar Baron

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The logistical network of a company is adaptive, so co-evolves with the environment, constantly changing their connections with suppliers, and internally among its staff structure and processes with distributors, dealers and customers. This coupled with the dynamic growth of organizations, the use of information systems and technologies, the diversity of products and the high degree of market uncertainty, leading to the logistics network of an organization become complex. Understand and set limits to the complexity implies an intention to control and therefore a set of measures that allow the decision maker to identify intervention points in the logistics network and guide the ecoevolution intentionally structuring the logistics system and making more efficient provider network , operational network and the customer.Here, a measuring dynamic variable describing the overall complexity of the system and therefore the associated network structure is proposed.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014
EditorsFatos Xhafa, Mario Koeppen, Francesco Palmieri, Vincenzo Loia, Leonard Barolli
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages504-508
Number of pages5
ISBN (Electronic)9781479963867
DOIs
StatePublished - Mar 9 2014
Externally publishedYes
Event6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 - Salerno, Italy
Duration: Sep 10 2014Sep 12 2014

Publication series

NameProceedings - 2014 International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014

Conference

Conference6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014
CountryItaly
CitySalerno
Period9/10/149/12/14

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

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