A Multi-Agent Approach Towards Collaborative Supply Chain Management

Supply chain collaboration has become a critical success factor for supply chain management and effectively improves the performance of organizations in various industries. Supply chain collaboration builds on information sharing, collaborative planning and execution. Information technology is an important enabler of collaborative supply chain management. Many information systems have been developed for supply chain management from legacy systems and enterprise resource planning (ERP) into the newly developed advanced planning and scheduling system (APS) and e-commerce solutions. However, these systems do not provide sufficient support to achieve collaborative supply chain. Recently, intelligent agent technology and multi-agent system (MAS) have received a great potential in supporting transparency in information flows of business networks and modeling of the dynamic supply chain for collaborative supply chain planning and execution. This paper explores the similarities between multi-agent system and supply chain system to justify the use of multi-agent technology as an appropriate approach to support supply chain collaboration. In addition, the framework of the multi-agent-based collaborative supply chain management system will be presented

Exploring the Use of Computer Simulations in Unraveling Research and Development Governance Problems

Understanding Research and Development (R&D) enterprise relationships and processes at a governance level is not a simple task, but valuable decision-making insight and evaluation capabilities can be gained from their exploration through computer simulations. This paper discusses current Modeling and Simulation (M&S) methods, addressing their applicability to R&D enterprise governance. Specifically, the authors analyze advantages and disadvantages of the four methodologies used most often by M&S practitioners: System Dynamics (SO), Discrete Event Simulation (DES), Agent Based Modeling (ABM), and formal Analytic Methods (AM) for modeling systems at the governance level. Moreover, the paper describes nesting models using a multi-method approach. Guidance is provided to those seeking to employ modeling techniques in an R&D enterprise for the purposes of understanding enterprise governance. Further, an example is modeled and explored for potential insight. The paper concludes with recommendations regarding opportunities for concentration of future work in modeling and simulating R&D governance relationships and processes

MODERN APPROACHES TO MODELING THE MANAGEMENT OF ENTERPRISE INVESTMENT RESOURCES

Introduction. In spite of the considerable scientific results obtained by Ukrainian and foreign scientists in the field of management of socio-economic processes and systems, many problems remain and they are related to the improvement of the principles and mechanisms of management of investment resources of the enterprise, which, in turn, is due to the lack of a single , universally recognized in the business world, an effective science-based approach to modeling the management of enterprise investment resources. Purpose. The purpose of this study is to analyze modern approaches to modeling the management of enterprise investment resources to form a methodological basis that will absorb most of the benefits of well-known schools and approaches. Results. The methodology of economics and mathematical modeling, which is the basis of the concept of forming an economic-mathematical model of management of investment resources of the enterprise, allows us to carry out an analysis of the processes of functioning of the investment activity of the enterprise, as well as to formalize the processes of optimization and planning of investment resources at the enterprise. Conclusions. At the present stage of the theory and practice development of management, all preconditions for the further development of management systems of socio-economic systems were created by complicating their information structure, computerization, intellectualization (both their individual components and systems in general). The priority of scientific research in this area is the rational synthesis of the cybernetic approach with multi-agent, reflexive and other approaches to modeling the management of investment resources at the enterprise in order to combine modern computing power of information systems with the results of scientific and applied research in the field of economic systems management at all levels

Development of an Automated System for Analysis, Modeling, and Decision-Making for Metallurgical Enterprise

The paper presents development of an automated system for analysis, modeling, and decision-making for metallurgical production. When operating information systems at various levels of automation, there is a problem of system integration at the level of information exchange to support timely decision-making. Problem solutions are aimed at implementing a typical business process for changing (improving) the technological, logistic, and organizational processes of the enterprise. The paper describes a scheme for integrating the processes of metallurgical production improving based on the use of a multi-agent approach in development of modules of the automated system. The use of the multi-agent approach allows solving the problem of automating the processes of approval and decision-making through the communication of hybrid agents implementing the functionality of individual modules of the system. © 2022 American Institute of Physics Inc.. All rights reserved.Government Council on Grants, Russian FederationA decision support method based on a multi-agent approach was used when developing the AMD system. This method is supported by the BPsim software package [18], which allows describing hybrid agents using production and frame knowledge bases. The BPsim tool includes the following integrated products: systems for dynamic situation modeling and decision support, CASE tool

Modeling and Execution of Multienterprise Business Processes

We discuss a fully featured multienterprise business process plattform (ME-BPP) based on the concepts of agent-based business processes. Using the concepts of the subject-oriented business process (S-BPM) methodology we developed an architecture to realize a platform for the execution of distributed business processes. The platform is implemented based on cloud technology using commercial services. For our discussion we used the well known Service Interaction Patterns, as they are empirically developed from typical business-to-business interactions. We can demonstrate that all patterns can be easily modeled and executed based on our architecture. We propose therefore a change from a control flow based to an agent based view to model and enact business processes.Comment: arXiv admin note: substantial text overlap with arXiv:1404.273

Multi Site Coordination using a Multi-Agent System

A new approach of coordination of decisions in a multi site system is proposed. It is based this approach on a multi-agent concept and on the principle of distributed network of enterprises. For this purpose, each enterprise is defined as autonomous and performs simultaneously at the local and global levels. The basic component of our approach is a so-called Virtual Enterprise Node (VEN), where the enterprise network is represented as a set of tiers (like in a product breakdown structure). Within the network, each partner constitutes a VEN, which is in contact with several customers and suppliers. Exchanges between the VENs ensure the autonomy of decision, and guarantiee the consistency of information and material flows. Only two complementary VEN agents are necessary: one for external interactions, the Negotiator Agent (NA) and one for the planning of internal decisions, the Planner Agent (PA). If supply problems occur in the network, two other agents are defined: the Tier Negotiator Agent (TNA) working at the tier level only and the Supply Chain Mediator Agent (SCMA) working at the level of the enterprise network. These two agents are only active when the perturbation occurs. Otherwise, the VENs process the flow of information alone. With this new approach, managing enterprise network becomes much more transparent and looks like managing a simple enterprise in the network. The use of a Multi-Agent System (MAS) allows physical distribution of the decisional system, and procures a heterarchical organization structure with a decentralized control that guaranties the autonomy of each entity and the flexibility of the network