SHS Web Conf.
Volume 35, 20173rd International Conference on Industrial Engineering (ICIE-2017)
|Number of page(s)||7|
|Section||Sustainable Development of Industrial Enterprises|
|Published online||26 June 2017|
Implementation of information and analysis support of the industrial enterprise’s logistical management based on the tools of the fuzzy set theory
South Ural State University, Chelyabinsk, Russia
* Corresponding author: email@example.com
Management of industrial enterprises’ logistical systems is based on application of rather heterogeneous and not always certain information. Presence of different types of uncertainty in the complex hierarchical system of industrial enterprises’ logistical management gives grounds for analysis support of management solutions based on the fuzzy set theory. Use of the fuzzy set theory allows to link together and adequately consider all the necessary heterogeneous information. In this regard, information on functioning of the logistical system must be presented in a specific form as membership functions. It is justified in the article that the tools of the fuzzy set theory can be applied for description of parameters of the industrial enterprises’ logistical system and justification of decision-taking in the sphere of logistical management. Within the framework of the system of information and analysis support of industrial enterprises’ logistical management it is proposed to use tools of problem “determination of the fuzzy set image” and its variety – “definition of the sub direct fuzzy set image” in order to choose the best variant of combination of key efficiency indicators of logistical management complying with the present complex of criteria. Application of the fuzzy set theory also allows to determine fuzzy values of factors, as a result of which the enterprise’s logistical system has obtained the existing or objective set of features. For analysis of factors influencing the key efficiency indicators of the industrial enterprise’s logistical management it is proposed to use tools of problem “definition of the fuzzy set pre-image at a fuzzy binary relation”.
© Owned by the authors, published by EDP Sciences, 2017
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