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Research Centre for Operations Research and Statistics (ORSTAT), Leuven

Research Group

Lifecycle:1 Oct 1997 →  Today
Organisation profile:

In operations research, a challenging research area is combinatorial optimization. Next to exact methods such as branch-and-bound, branch-and-price, also approximation algorithms are studied. Assignment and scheduling problems, winner determination problems and research on client-oriented vehicle routing problems are some of the subjects under study. Further emphasis is placed on machine scheduling, resource-constrained project planning and on project portfolio management. Deterministic approaches as well as methods taking the uncertainty into account are investigated. Additionally, nonparametric frontier based methods are studied both theoretically and empirically with applications in a variety of economic domains (e.g., finance, microeconomics and macroeconomics). 

The statistical research topics cover a range of challenging research subjects. Currently, important topics arising with the availability of data in high dimensions are investigated, as well as topics related to the analysis of incomplete data. This requires dealing with identifiability, estimation and variable selection under sparsity, computational algorithms, robustness, and hypothesis testing. The results can be used in time series analysis, for graphical modeling of e.g. medical data, and for the analysis of duration data, coming from e.g. unemployment studies. Another research area is the design and analysis of experiments with applications in industry, marketing, transportation and health economics.

Next to the methodological research, ORSTAT investigates computational aspects, both for statistics and for operations research. In this way the applicability of the proposed methods is facilitated and often software is made available through websites.


Keywords:Quantitative methods, Operations Research, Business Statistics
Disciplines:Applied mathematics in specific fields, Statistics and numerical methods, Applied economics