Plenary Speakers

 

Granularity — a bridge between continuous and discrete optimization

In this talk we sketch the development of the granularity concept in optimization over the past five
years. Granularity relaxes the difficulties imposed by integrality conditions and often provides ways
for determining good feasible points of mixed-integer optimization problems at low computational cost.

Starting from error bound results for roundings in mixed-integer linear optimization, we illustrate
how this concept unfolded to provide algorithms for the computation of feasible points in mixed-integer
linear, convex and nonconvex optimization. We also comment on the treatment of equality constraints and
explain the integration of the granularity idea into branch-and-bound frameworks.

 

  • EUROPT Fellow 2020 Lecture by Manlio Gaudioso (Universita della Calabria, Italy)

 

  • EUROPT Fellow 2021 Lecture by Monique Laurent (Centrum Wiskunde & Informatica, Netherlands)

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