Algorithms and OR

 

Solving large computational problems from various application areas such as production, logistics, traffic, and science requires the application of advanced analytical and algorithmic methods. With the rapidly increasing amount of a data, the problem instances that need to be solved become larger and larger. This so-called big data challenge makes even more important to invest into foundational and applied algorithmic research. Before one can choose the right algorithmic framework or design a specific algorithmic solution that is tailored to the problem at hand, a significant amount of effort must be spent into modeling and understanding a problem. All these steps require the rigorous application of mathematical methods.

The design and analysis of algorithms is a central topic in various research disciplines. Within computer science a focus lies on the design and analysis of algorithms with provable performance guarantees and in investigating the computational complexity of algorithmic problems. Operations Research (OR) deals with the application of advanced analytical and algorithmic methods to help make better decisions in economic contexts covering areas such as management science and business analytics.

Employing techniques from mathematical sciences, such as formal modeling, statistical analysis, and mathematical optimization, algorithm design and operations research arrives at optimal or near-optimal solutions to complex decision-making problems. It encompasses a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency, such as simulation, mathematical optimization, queuing theory, Markov decision processes, economic methods, data analysis, statistics, neural networks, expert systems, and decision analysis. Nearly all of these techniques involve the construction of mathematical models that attempt to describe the system. (With changes quoted from: www.informs.org).

Main applications areas (adopted from the CFP of EURO 2009):

1. Continuous optimization and control
2. Data mining; knowledge discovery; artificial intelligence
3. DEA and performance management
4. Decision analysis; decision support systems; modelling languages
5. Discrete optimization; graphs & networks
6. Energy, environment & climate
7. Financial modelling; risk management; banking
8. Fuzzy sets; softcomputing
9. Game theory; mathematical & experimental economics
10. Health, life sciences & bioinformatics
11. Location; logistics; transportation; traffic
12. Metaheuristics & biologically inspired approaches
13. Multiple criteria decision making, optimization & group decision
14. OR education, history & ethics
15. OR for developing countries
16. OR in agriculture & natural resources
17. OR in industries & software applications
18. Production management; supply chain management
19. Revenue management & managerial accounting
20. Scheduling, time tabling & project management
21. Stochastic programming; stochastic modelling; simulation
22. System dynamics; dynamic modelling
23. Telecommunication & network analysis