The Orienteering Problem (OP) is a generalization of the well-known traveling salesman problem and has many interesting applications in logistics, tourism and defense. To reflect real-life situations, we focus on an uncertain variant of the OP. Two main approaches that deal with optimization under uncertainty are stochastic programming and robust optimization. We will explore the potentialities and bottlenecks of these two approaches applied to the uncertain OP. We will compare the known robust approach for the uncertain OP (the robust orienteering problem) to the new stochastic programming counterpart (the two-stage orienteering problem). The application of both approaches will be explored in terms of their suitability in practice.

robust optimization, stochastic programming, uncertain orienteering problem
Erasmus School of Economics
hdl.handle.net/1765/37193
Econometric Institute Research Papers
Report / Econometric Institute, Erasmus University Rotterdam
Erasmus School of Economics

Evers, L, Glorie, K.M, van der Ster, S, Barros, A.I, & Monsuur, H. (2012). The Orienteering Problem under Uncertainty Stochastic Programming and Robust Optimization compared (No. EI 2012-21). Report / Econometric Institute, Erasmus University Rotterdam (pp. 1–25). Erasmus School of Economics. Retrieved from http://hdl.handle.net/1765/37193