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Information technology (IT) is a prerequisite for successful supply chain management (SCM) today and will become even more so in near future. The logistics and SCM field is developing very dynamically. Business-to-business transactions are made via the Internet and enterprise resource planning (ERP) systems that manage the transactional information within the enterprise. While IT systems are vital components in supply chains, their successful management rests on intelligent and coordinated decision making throughout the logistics network. Intelligent decision support using advanced decision technologies are becoming increasingly important in logistics and SCM. Data warehouses and data mining can be used to store and analyze 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 technologies to support human agents in logistics and SCM is a very active field in research, consulting and software development. Many such technologies or systems have been implemented recently or are currently in the stage of implementation. 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 seek papers dealing with 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, descriptive models, data warehousing, and data mining. We are especially interested in real-world applications and in software solutions which assist in solving decision problems. This is extended towards, e.g., advanced planning systems and the intelligent use of enterprise resource planning 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.