The purpose of this program is to stimulate research cooperation between Europe and South America in the field of uncertainty in combinatorial optimization. Combinatorial optimization is a lively field in mathematics and computer science. It aims at finding a best solution among a finite or countably infinite number of solutions. In standard optimization techniques, we assume that all the relevant data to the problem are completely known. However, this assumption is not always realistic. In many scenarios, we need to optimize when the data is not fully available and decisions with wide-ranging implications have to be made in the face of incomplete data. In this project, we study methods for dealing with uncertainty in combinatorial optimization. We will study three different models for uncertainty. The first one is online optimization in which decisions have to be made without any knowledge of future information to be released. A second model is stochastic optimization in which the uncertainty is modeled by the assumption that part of the data is given only by probability distributions. The third model for uncertainty is by an algorithmic game theory approach. Here it is assume that the solution is obtained by the interaction of a multitude of autonomous agents, each of which is holding private information. Therefore, there is no centralized control that has access to all relevant input data and that is able to enforce the computed solution as the final outcome. The objectives of this international research staff exchange prgoram are: 1. Intensify th ejoint research in optimization under uncertainty among researchers in Europe and South America 2. Training of junior researchers 3. Disseminate and transfer knowledge obtained during the program among academics in South America and the European Research Area.
Fields of science
Call for proposal
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