In a classical vehicle routing problem (VRP), customer demands are known with certainty. On the other hand, in real-life problems, customer demands may change over time. Therefore, in the classical VRP, the assumption that customer demands are stochastic should be taken into account.
- Speaker
- Date
- Friday 26 Sep 2025, 12:00 - 13:00
- Type
- Seminar
- Room
- ET-14
- Building
- E Building
To expedite consumer demands and minimize fuel use and carbon emissions, organizations must concurrently address client distribution and collection requirements. Customers' distribution requirements can be predicted, but it is impossible to predict in advance the product requirements they will send for recycling. Hence, in this study, a mathematical programming model is developed for the multi-depot simultaneous pick-up and delivery vehicle routing problem under the assumption that customers' picking demands are stochastic. However, there are non-linear constraints in the developed model. Thereby, firstly, the stochastic model is linearized, and then the effectiveness of the model is analyzed. The efficacy of the linearized model is ascertained by generating test problems. The study investigated the impact of varying reliability levels and the number of depots on the model. As a result of the sensitivity analysis, it was determined that by decreasing the reliability level, the solution time of the problems decreased and the number of problems reaching the best solution increased. In the study, 135 test problems were solved by changing the reliability level, and the best result was achieved in 105 of these problems within 7200 s. The increase in the number of depots both reduced the solution time of the problems and was effective in reaching the best solution for all solved test problems.
About the speaker
Beste Desticioglu Tasdemir is an Associate Professor at the Department of Operations Research at the Alparslan Defense Sciences and National Security Institute of the National Defense University, Türkiye. Beste received her PhD in Industrial Engineering from Gazi University, Türkiye, where she also completed her bachelor’s and master’s degrees. Her research interests include Operations Research, Logistics and Supply Chain Management, and Multi-Criteria Decision Making. She has published numerous peer-reviewed articles in Turkish and English, thirteen book chapters, and several national and international conference papers.
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Lunch will be provided (vegetarian option included).
For more information please contact the Secretariat Econometrics at eb-secr@ese.eur.nl