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2988. Distributionally robust fixed interval scheduling with heterogenous machines and random delays
Invited abstract in session WC-35: Robust Optimization: Theory and Applications, stream Stochastic, Robust and Distributionally Robust Optimization.
Wednesday, 12:30-14:00Room: 44 (building: 303A)
Authors (first author is the speaker)
| 1. | Monika Matoušková
|
| Department of probability and mathematical statistics, Charles University |
Abstract
We deal with operational fixed interval scheduling problem where start times are given and the actual finishing times can be influenced by random delays. We further consider heterogeneous case, i.e., multiple job and machine types. And we assume that the multivariate distribution of delays follows an Archimedean copula. We consider the highest worst-case probability that the schedule remains feasible, where given proportion of marginal distributions of delays are stressed. This problem has an interesting reformulation containing a commonly used risk measure. We implement a decomposition algorithm. A possible application is gate assignment problem where incoming flights have to be assigned to available gates of an airport. In this problem, heterogeneity is caused by the fact that different aircrafts might need to be assigned to different gates. Moreover, there can be proportion of flights where worse delays occur.
Keywords
- Stochastic Optimization
- Scheduling
Status: accepted
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