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Dynamical systems theory and algorithms for NP-hard problems. (English) Zbl 1528.37072

Junge, Oliver (ed.) et al., Advances in dynamics, optimization and computation. A volume dedicated to Michael Dellnitz on the occasion of his 60th birthday. Cham: Springer. Stud. Syst. Decis. Control 304, 183-206 (2020).
Summary: This article surveys the burgeoning area at the intersection of dynamical systems theory and algorithms for NP-hard problems. Traditionally, computational complexity and the analysis of non-deterministic polynomial-time (NP)-hard problems have fallen under the purview of computer science and discrete optimization. However, over the past few years, dynamical systems theory has increasingly been used to construct new algorithms and shed light on the hardness of problem instances. We survey a range of examples that illustrate the use of dynamical systems theory in the context of computational complexity analysis and novel algorithm construction. In particular, we summarize a) a novel approach for clustering graphs using the wave equation partial differential equation, b) invariant manifold computations for the traveling salesman problem, c) novel approaches for building quantum networks of Duffing oscillators to solve the MAX-CUT problem, d) applications of the Koopman operator for analyzing optimization algorithms, and e) the use of dynamical systems theory to analyze computational complexity.
For the entire collection see [Zbl 1445.37003].

MSC:

37M99 Approximation methods and numerical treatment of dynamical systems
68Q17 Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.)
68W40 Analysis of algorithms
90C27 Combinatorial optimization
90C60 Abstract computational complexity for mathematical programming problems

Software:

Concorde; LKH

References:

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