ESTEBAN SALGADO

PhD Graduate

PhD program:: XXXIV


supervisor: Laura Palagi

Thesis title: Methods for non-linear optimisation problems on graphs

Combinatorial optimization is the domain that is concerned with, given a problem with discrete variables (combinatorics), finding among a given set of possible configuration of the variables (feasible set) the best solution, in terms of minimizing or maximizing a function in the feasible set (optimization). Most combinatorial optimization problems are defined on graphs. This type of problems tend to be hard to solve (usually being NP-hard) and therefore different approaches need to be used in order to solve them. Two problems are studied in this thesis. The Maximum Cut problem (Max-Cut) for which a heuristic based on the subgraph sampling method is used to improve the state-of-the-art over a large testbed including instances coming from different types of graphs. And the Direct Current Optimal Transmission Switching, for which a separation procedure based on the cycles of a power network is proposed. The state-of-the-art regarding this separation problem was constrained to a fixed subset of the cycles of the graph. In this work is presented a general approach that does not consider a fixed set.

Research products

11573/1619080 - 2019 - Perspective cuts for the ACOPF with generators
Salgado, Esteban; Gentile, Claudio; Liberti, Leo - 04b Atto di convegno in volume
conference: 47th International Conference on Optimization and Decision Science, ODS 2018 (Taormina; Italy)
book: New Trends in Emerging Complex Real Life Problems - (978-3-030-00472-9)

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