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- Title
Preface.
- Authors
Liberti, Leo; Sager, Sebastian; Wiegele, Angelika
- Abstract
Currently, for generic MINLP for which no structure is known in advance, the best exact[2] algorithm for solving MINLP is the spatial Branch-and-Bound (sBB) algorithm. This special issue of Mathematical Programming series B collects papers authored (or co-authored) by researchers who attended the second Oberwolfach workshop on MINLP, titled "Mixed-integer Nonlinear Optimization: a hatchery for modern mathematics", and co-organized by the guest editors of this special issue. On the one hand such I mixed-integer optimal control i (MIOC) problems are a generalization of MINLPs, because the problem formulations allow for trivial special cases with HT <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>n</mi><mi>x</mi></msub><mo>=</mo><mn>0</mn></mrow></math> ht differential states that are formally equivalent to a MINLP. The sBB algorithm is a variant of the Branch-and-Bound (BB) algorithm, which was introduced in [[32]] and extended to (separable) Nonlinear Programming (NLP) in [[17]].
- Subjects
MATHEMATICAL programming; NONCONVEX programming; DIFFERENTIAL-algebraic equations; TURING machines; DUALITY theory (Mathematics); HILBERT'S tenth problem; SYMBOLIC computation
- Publication
Mathematical Programming, 2021, Vol 188, Issue 2, p411
- ISSN
0025-5610
- Publication type
Editorial
- DOI
10.1007/s10107-021-01687-2