K-ADAPTABILITY IN STOCHASTIC COMBINATORIAL OPTIMIZATION UNDER OBJECTIVE UNCERTAINTY

A seminar by Prof. Jonas Prünte (TU Dortmund)

  • Date: 30 MAY 2019  from 11:00 to 13:00

  • Event location: Aula 5.2 - Viale Risorgimento, 2 - DEI Bologna

  • Type: Seminar

We address combinatorial optimization problems with uncertain objective functions, given by discrete probability distributions. 

Within this setting, we investigate the so-called K-adaptability approach: the aim is to calculate a set of K feasible solutions such that the objective value of the best of these solutions, calculated in each scenario independently, is optimal in expectation.

We show that the problem is NP-hard even if the underlying certain problem is trivial, and present further complexity results concerning approximability and fixed-parameter tractability with respect to K.

Moreover, we present exact solution methods as well as a heuristic for this problem, and compare them in an extensive experimental evaluation.

Joint work with Prof. Christoph Buchheim

 

Contacts

Prof. Michele Monaci

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