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pro vyhledávání: '"Chassein, André"'
The paper deals with a multiobjective combinatorial optimization problem with $K$ linear cost functions. The popular Ordered Weighted Averaging (OWA) criterion is used to aggregate the cost functions and compute a solution. It is well known that mini
Externí odkaz:
http://arxiv.org/abs/1804.03594
We consider robust combinatorial optimization problems where the decision maker can react to a scenario by choosing from a finite set of $k$ solutions. This approach is appropriate for decision problems under uncertainty where the implementation of d
Externí odkaz:
http://arxiv.org/abs/1802.05072
We consider robust shortest path problems, where the aim is to find a path that optimizes the worst-case performance over an uncertainty set containing all relevant scenarios for arc costs. The usual approach for such problems is to assume this uncer
Externí odkaz:
http://arxiv.org/abs/1802.04149
In this paper the problem of selecting $p$ out of $n$ available items is discussed, such that their total cost is minimized. We assume that costs are not known exactly, but stem from a set of possible outcomes. Robust recoverable and two-stage models
Externí odkaz:
http://arxiv.org/abs/1701.06064
Autor:
Goerigk, Marc, Chassein, André
As most robust combinatorial min-max and min-max regret problems with discrete uncertainty sets are NP-hard, research into approximation algorithm and approximability bounds has been a fruitful area of recent work. A simple and well-known approximati
Externí odkaz:
http://arxiv.org/abs/1611.09754
Autor:
Chassein, André, Goerigk, Marc
In classic robust optimization, it is assumed that a set of possible parameter realizations, the uncertainty set, is modeled in a previous step and part of the input. As recent work has shown, finding the most suitable uncertainty set is in itself al
Externí odkaz:
http://arxiv.org/abs/1610.05127
Autor:
Chassein, André, Goerigk, Marc
In robust optimization, the general aim is to find a solution that performs well over a set of possible parameter outcomes, the so-called uncertainty set. In this paper, we assume that the uncertainty size is not fixed, and instead aim at finding a s
Externí odkaz:
http://arxiv.org/abs/1606.07380
Autor:
Chassein, André, Goerigk, Marc
Publikováno v:
In Discrete Applied Mathematics 15 June 2021 296:141-163
Autor:
Chassein, André, Kinscherff, Anika
Publikováno v:
In Computers and Operations Research April 2019 104:228-238
Autor:
Chassein, André, Goerigk, Marc
Publikováno v:
In Computers and Operations Research February 2016 66:181-189