Intelligent Decision Support and Big Data for Logistics and Supply Chain Management Minitrack
Information technology (IT) and information systems (IS) are prerequisites and enablers for successful supply chain management (SCM). With related advances, the logistics and SCM field is developing very dynamically. Business-to-business transactions are made via the Internet and enterprise resource planning (ERP) systems support managing the transactional information within the enterprise. Cooperation and coordination is only possible based on IT and IS. While IT and IS are vital components in supply chains, their successful management rests on intelligent and coordinated decision making throughout the logistics network. Intelligent decision support and decision analytics using advanced decision technologies and analytics methodology are of utmost importance in logistics and SCM. Sensor networks, social network activities, RFID deployment, internet search histories and retail transactions are just a few examples of sources to provide data to support efficient decision analytics. Big data issues are well recognized and offer opportunities long waited for but also provide challenges in handling and decision analytics. Cloud computing allows also small and medium sized enterprises to access resources to support analytics functions. Business intelligence and data mining can be used to store and analyze logistics, product, inventory, and sales information. Simulation and optimization, which can be found in advanced planning and scheduling systems, can be employed for, e.g., inventory, production, procurement, and distribution planning. Intelligent agents can, e.g., communicate with different partners in the supply chain, assist in collecting information, share product information, negotiate prices, and distribute alerts throughout the logistics networks. The design and implementation of intelligent decision analytics tools to support human agents in computational logistics and SCM is a very active field in research, consulting and software development. Many such technologies or systems are continuously being developed, implemented and used in real-world scenarios. We do, therefore, believe that this minitrack will be recognized by both the scientific community and practitioners developing or using logistics and SCM solutions.
We aim at organizing a minitrack consisting of two sessions depending on the number of high quality submissions. We seek papers dealing with decision analytics, business intelligence, big data, cloud computing and decision technologies which contribute to intelligent decision support in the whole field of logistics and in particular in all categories of SCM. This includes but is not restricted to simulation, optimization, heuristics, metaheuristics, agent technologies, decision analytics, descriptive models, and data mining. We are especially interested in real-world applications and in information systems and software solutions which assist in solving decision problems. This is extended towards, e.g., computational logistics, advanced planning systems and the intelligent use of ERP systems. Also conceptual ideas, reports on projects in progress, and case studies are welcome. Moreover, teaching cases both at the university as well as the executive level may be of interest.
Stefan Voß (Primary Contact)
University of Hamburg, Germany
RWTH Aachen University, Germany
University of Southern Denmark