Application of Artificial Intelligence Methods and Technologies in Digital Supply Chains
MAGAZINE №4 (99) August 2020
AUTHORS LYCHKINA N.N.
CATEGORY Analytics and reviews Information technologies in logistics and SCM Modern concepts and technologies in logistics and SCM Simulation modelling
ABSTRACT
The article provides analysis of the main directions and technologies of artificial intelligence and their application in digital supply chains; specifies prospects of intelligent information systems application to improve interorganizational cooperation and participants’ collaboration in integrated and network structures of supply chains. Particular attention is paid to the research of possibilities of modern multi-agent technologies and intelligent systems in supply chain management aimed at interorganizational cooperation of partners, conflict management and consensus reaching between network partners, real time risk management, dynamically reconfigurable network structure formation of supply chains.
Keywords: supply chain management Artificial Intelligence AI knowledge management multiagent systems digital twin
Influence of Digitalization on Logistics Systems Organization and Functioning Processes
MAGAZINE №5(88) October 2018
AUTHORS
GRIGOREV M.N. - Cand. of Eс. Sc., Associate professor, St. Petersburg State University of Economics (St. Petersburg, Russia)
CATEGORY Analytics and reviews Information technologies in logistics and SCM Simulation modelling
ABSTRACT
The results of the information technologies intensive development and implementation processes, recently defined as digitalization, were the basis of the significant changes in the domestic economy. At the same time, it is important to understand that digitalization process require an appropriate response in order to create an environment, which promote to development of strategically valuable economic sectors, include the industrial manufacturing. These circumstances determined the motivation of implementing at the state level such programs as the Digital Economy and the National Technological Initiative, that are aimed at creating conditions for the development of industry in the context of the digitalization.
Focusing on the logistics systems and industrial enterprise supply chains functioning processes, it is important to note, that new opportunities are opened due to development and implementation of information technologies in the economy digitalization context. These opportunities consist in the exchange of information between the individual production, logistics and auxiliary systems and their elements, as well as the products and the external environment, which in general will allow forming big data sets. Herewith, the result of processing the relevant data sets will form basis of the continuous improvement processes through self-organization and self-decision by the active system components.
At the initial stages of the study, a literature overview was done in the field of logistics system organizing within the contemporary concepts of industrial production development, including the Industry 4.0 concept. This has shown that on the one hand, there is a significant impact of digitalization processes on the organization and functioning of logistics system, but on the other hand, there is a lack of methodological developments in the area of these systems design.
For this reason, it is important to investigate the development of instruments for justification of logistics processes functioning characteristics within digitalization context. For this, a generalized structure of the digital logistics system was offered and the requirements for the functioning processes were determined. Taking into account a special aspects of this structure and functioning requirements, we offered to use simulation modeling tools in the organizational design problems. It is proposed to use traditional paradigms of simulation, which include discrete-event and agent-based modelling. On a separate note the possibility of applying the approach at the junction of these two paradigms, which implying the use of their main advantages: using the discrete-event modeling in the simulation of functioning process where the logistics system is describes as the multi-agent environment.
Keywords:
Methods and Tools of Intelligent Data Analysis for Digital Logistics and Supply Chain Management
MAGAZINE №4(87) August 2018
AUTHORS
SEROVA E.G. - Cand. of Ec. Sc., Associate Professor Management Department, National Research University Higher School of Economics (St. Petersburg, Russia)
CATEGORY Analytics and reviews Information technologies in logistics and SCM
ABSTRACT
Success of any logistics enterprise in the context of digital economy progress directly depends on regular and effective innovations in the area of improving analytical applications and information systems in such actively developing fields of knowledge as strategic management, distribution networks development, and supply chain management. In an attempt to ensure a sustainable economic circumstance under conditions of strong competition, the most perspective companies are increasingly focusing on the development and introduction of modern methods and tools for intelligent data analysis. The article focuses on the consideration of issues related to the use of modern simulation approaches and such components of the soft computing concept as neural networks, fuzzy logic and evolutionary computations in solving problems of multifunctional logistics and supply chain management.
Keywords:
Multi-agent systems in logistics: analysis of experience and perspectives
MAGAZINE №2 (64) April 2015
AUTHOR MOROZOVA Y.A.
CATEGORY Information Technology in Logistics and SCM Simulation Planning the supply chain
ABSTRACT
Constant changes in demand for resources in the market complicate planning and management of material flows. In current practice, it’s possible to solve this problem by applying multi-agent systems. The article considers models, technologies, the typical architecture of multi-agent system, analyzes of completed projects and describes the prospects for the development of multi-agent systems in logistics
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