Working Paper Series
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Stability in a Specialized Supply Chain Setting Issue No. 61 (April - May 2010)
 The stable Supply Chain Network (SCN) configuration, introduced by Ostrovsky [11], is defined on a finite set of agents A that can be divided into k finite disjoint sets, A1 being the set of suppliers, Ak the set of final consumers, and Ai, i={2,3,…,k-1}, the sets of intermediary agents, and asks for a chain stable allocation of the agents. In our current work we present a specialized version of Ostrovsky’s generic framework, and prove that, under this setting, any k-sided SCN can be decomposed to k-1 united SM sub-markets. Moreover, we implement T-algorithm, presented in [11], as a generalization of the Gale-Shapley algorithm [7], and show how an intermediary-optimal solution can be derived, while we prove that the lattice formed by the set of solutions is distributive. Download  List of working papers |
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Center of Studies on Business Intelligence and Database
Scientific Coordinator: Dr Damianos Chatziantoniou,
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Research streams -
Data Warehousing -
Multi-Dimensional Analysis, Decision Support and OLAP -
Data Mining and Knowledge Discovery in Databases -
Data Stream Management Systems -
Management of RFID Data Sets -
Data Models, Query Languages and Optimization
Research Objectives -
Perform basic research on all aspects of data warehousing: ETL processes, implementation and maintenance of data cubes, data modelling and design principles, query processing and optimization, indexing methods, tools. Develop languages, algorithms and tools to express easily and evaluate efficiently complex data analysis reports. Current work involves large telecom, internet, financial and healthcare data sets. -
Develop best practices, derive success factors and understand common pitfalls of Business Intelligence implementations in the Greek public and private sectors. -
Data stream systems are the focus of intense research activities -
Sensor measurements, financial data, network packets and RFID data can all be seen as data streams. The ability to analyze data streams at real time is of increasing importance and has been identified as a crucial element for modern organizations and agencies. There are many open issues under investigation, such as how to model data streams, what is the best architecture for stream management systems, what kind of reports are appropriate, how to warehouse, index and mine stream data, etc.
Researchers
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