Generic algorithms for predictive refillment scheduling in SCM-systems of large retail companies
The article contains a description of generic predictive refillment scheduling algorithm.
A powerful and effective store network administration sites, a smooth running of a business, quality items or potential benefits, consequently escalating client trust and business picks up. To land at this phase in an association's business outgrowth all rely upon the best choices that must be taken to move the correct way. These choices are normally aftereffects of past events and outside information that have been incorporated to give data or learning. For this reason, a decision support system is hereby proposed to be able to pool data from the 3 main decision Phases of a Supply Chain Management - (1) Supply chain Design (Strategy) phase, (2) Decision in Supply Chain Planning (Management) phase, and (3) Operational level phase. This Proposed framework is pointed and boosting basic leadership process, by giving brought together data to help the hierarchical basic leadership process.
Supply Chain Management in modern conditions requires close integration of business processes of transport companies and information technology. We know that today there are a large number of applications and information systems for the automation of logistics activities. Currently there is no complete and consistent classification of software products of the Transportation Management System (TMS). Their diversity is relevant in the context of the fourth industrial revolution ("Industry 4.0"). It's difficult to navigate existing and emerging information systems and choose the most appropriate. The most important class TMS products are designed to plan, organize, and account for the operation of the vehicle fleet. However, their practical use is often ineffective for several reasons. One of the common problems in the implementation of the information system is the lack of or inadequate investigation of all operating activities of the enterprise and its strategic position in the market, the analysis of information flows, evaluation of employees of business roles, mechanism of decision-making. The reason for this is the lack of logistics management competencies in the field of information technology, and on the other hand, often poor understanding of IT-managers of the transport processes. Therefore, a practical approach synchronization strategic goals, objectives, business processes, supply chain management with business logic implemented information system. The paper discusses the use of proper Zachman enterprise architecture framework as this approach. This proper framework is simple enough to understand, and is known for a long time in the IT industry. Therefore, its use in the development of the information supply chain management system in practice, it seems appropriate for small and medium-sized freight enterprises. It is known that the business processes of all transport companies in general are often very similar. However, in practice often requires a flexible adaptation of the information system for each of them.
The paper discusses dynamic aspects of developing supply chains and the potential of the simulation modeling method and paradigms in achieving strategic goals of supply chain management, focused on efficient integration, inter-organizational coordination and long-term strategies of stakeholder’s cooperation, as well as implementation of modern logistics technologies based on partner cooperation. By benchmarking various simulation paradigms, the authors demonstrate that АВМS best fits the purpose of describing inter-organizational coordination processes and cooperation within a supply chain.
In the field of supply chains transformation and strategic development there is a strong need in concurrent and aligned usage of different supply chain representations. That defines the approach to building generic supply-chain representation based on composite simulation models. The objective of this paper is to suggest a conceptual scheme and stratification approaches that enables creation of a model reflecting polysystemic representation of supply chain . The following base levels of supply chain representation are considered: object-based, configuration/network-based, process-based, and logistics coordination levels. Depending on addressable tasks of supply chain analysis and synthesis, process and system dynamic simulation models of different degrees of detail may be used. Agent-based modeling is used to model interorganizational coordination between supply chain partners.
The application opportunities to the supply chain management of such scientific branches as the Graph theory, Social Network Analysis are shown. Using simulations, it is shown how supply chain characteristics can influence of the results of the product on the market.
To serve target customers better than their competitors, supply chain management (SCM) teams today look into new technologies such as Big Data, Internet of Things (IoT) and Blockchain. These new technologies allow managers to develop and provide complex supply chain services and products faster with improved reliabilities. With these technologies, SCM teams can build complex models of a supply chain or systems of supply chains using a data-driven approach. With the growth of aviation domain across the world, there has been increasing demand in aircraft for airlines and other customers. In this domain, SCM teams deal with complex networked supply chains for aircraft’s spare part purchase and delivery for aircraft’s maintenance and repair. Aircraft’s spare parts are shipped to single assembly hubs, located globally. All parts come with certain life expectancy, specific requirements and maintenance attributes. With thousands of spare parts, hundreds of parameters, and number of manufactures distributed globally, SCM team need to deal with very large amount of data. In this paper, we use an industrial scenario of aviation industry SCM to demonstrate the necessity of having decentralized system based on distributed data-driven application technologies such as Blockchain, not only to assist in maintaining inventory of the aircraft’s parts but also to monitor the performance, usage, etc. This will help to achieve a transparent network of supply chain for aircraft’s parts and reduce the risk of availability of aircraft’s parts in black market. These new data-driven technologies when embedded into SCM scenarios will help the SCM managers to analyse the supply, demands, source of availability of spare parts and provide methods to procure them from the right sources.
It gives us great pleasure to welcome you on the 17th edition of the International Conference on Harbor, Maritime & Multimodal Logistics Modeling and Simulation (HMS 2015) part of the 12th International Multidisciplinary Modeling and Simulation Multiconference (I3M). HMS 2015 upholds a long tradition started in 1999 in the field of simulation and computer technologies applied to logistics, supply chain management, multimodal transportation, maritime environment and industrial logistics. As time goes by, HMS looks at the future of science and practice seeking to capture new and emerging development trends but not only. As challenges are put forward by the fast changing social, technical and economic situation, a great effort has been done to set up an advanced scientific program with lots of talks, seminars, research presentations and discussions. Valuable research experiences need to be shared for developing new knowledge and generating new groundbreaking ideas. This is, in essence, the inner meaning that HMS nurtures. Therefore HMS gives a not‐to‐be‐missed chance of networking among colleagues to set up new relations and strengthening long‐established ties on joint research interests. It’s our firm determination that HMS 2015, as indeed past and future editions, could end with some strong take‐home messages rewarding merits and scientific excellence. To this end, HMS provides the Authors of the best papers with the opportunity to extend their works for publication in International Journals Special Issues.