Community Research and Development Information Service - CORDIS


EUSACOU — Result In Brief

Project ID: 247574
Funded under: FP7-PEOPLE
Country: Netherlands

A transatlantic approach to tackle 'uncertainty'

Many complex everyday problems involve finding the best of all possible solutions. An EU-funded project brought together scientists from both sides of the Atlantic Ocean to study effective algorithms for cleverly solving such problems.
A transatlantic approach to tackle 'uncertainty'
Most optimisation problems in real life do not have accurate estimates of parameters, such as costs and demands. At best, a probability distribution over the parameter values is known. Classical optimisation approaches are not useful in these cases, as the optimal solution found can be very sensitive to the slightest change in problem parameters.

Both Europe and South America possess expertise in mathematical programming and graph-theoretic algorithms dealing with this uncertainty for optimisation problems, representing a golden opportunity to collaborate in the field. This was the aim of the EU-funded project 'European South American network on combinatorial optimization under uncertainty' (EUSACOU).

To achieve its aims, EUSACOU fellows explored three different models for dealing with uncertainty. The first model, called online optimisation, assumes no knowledge of the future, whereas the second model, called stochastic optimisation, makes some guesses on what the future could be like. Finally, the third model involves a multitude of autonomous agents, each of which holds private information with no centralised access.

One application involved scheduling problems in which jobs may be split into parts to be processed simultaneously on more than one skilled machine. Optimisation problems of this kind are encountered when modelling the planning of disaster relief operations. Using newly developed approximation algorithms, EUSACOU fellows analysed the quality of scheduling policies and were able to glean valuable data.

Other uncertainty issues tackled pertained to social networks and to traffic assignment. For modern web search engines, EUSACOU fellows proposed and evaluated a static cache to speedup computation by exploiting results of queries that appeared in the past. Different approaches to populating the cache were examined to ultimately design a query resolution strategy offering substantial memory and time savings.

Junior researchers that received training within the EUSACOU project had the opportunity to share their findings during the closing workshop. The cross-fertilisation of ideas emerging from two continents is an excellent example of academic and research cooperation. This will likely attract talented researchers from abroad to work in Europe and open the European Research Area (ERA) to South America.

Related information


Uncertainty, optimisation problems, scheduling policies, social networks, search engines
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