The Top Eight Misconceptions about NP-Hardness

Mann, Zoltán Ádám

doi:10.1109/mc.2017.146

Cited by 8 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because FBS have limited power, energy, and speed, the lower the cost, the more efficient the trip [13]. This is an example of a Travelling Salesman Problem(TSP), which is a NP-hard (nondeterministic polynomial time hardness) problem in combinatorial optimization [14]. The TSP can be symmetric (STSP) or asymmetric (ATSP).…”

Section: Scheme Designmentioning

confidence: 99%

Deployment algorithms of UAV flying base stations based on 5G

Su¹,

Zhu²,

Yang³

et al. 2022

International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022)

View full text Add to dashboard Cite

show abstract

Section: Scheme Designmentioning

confidence: 99%

Deployment algorithms of UAV flying base stations based on 5G

Su¹,

Zhu²,

Yang³

et al. 2022

International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022)

View full text Add to dashboard Cite

show abstract

“…4 However, so far, no algorithm has been found that solves these problems with a computation time that scales polynomially with the size of the problem. 5 Therefore a lot of time and energy is required to solve the large-scale problems. 6,7 Because of this, a lot of research has been done on specialised hardware, dedicated to solving these problems and Ising machines have emerged as a promising candidate.…”

Section: Introductionmentioning

confidence: 99%

Improving photonic Ising machines by way of a stability analysis of steady states

Lamers,

Verschaffelt,

Van der Sande

2024

Machine Learning in Photonics

View full text Add to dashboard Cite

With increasing computational demands, the importance of efficient computer architectures rises. Photonic Ising machines offer a promising approach to address complex binary optimization problems by leveraging the speed and bandwidth inherent in photonic systems. When the cost function of an optimization problem can be mapped to the energy of an Ising problem, the ground state of the latter will represent the optimal solution. We conduct a stability analysis on this ground state of various benchmark problems. This analysis reveals that some benchmark problems are manageable for all Ising machine implementations. However, there are other problems for which the probability of achieving the ground state depends on the physical implementation. Our analysis shows the reasons for this advantage, leading us to formulate strategies to further enhance Ising machines and pave the way for future research. In future work, we will investigate if photonic Ising machines utilizing a different nonlinearity possess a distinct advantage in this context.

show abstract

Polynomial Algorithm for Solving Cross-matching Puzzles

Hynek

2021

Artificial Intelligence and Soft Computing

View full text Add to dashboard Cite

The Top Eight Misconceptions about NP-Hardness

Cited by 8 publications

References 5 publications

Deployment algorithms of UAV flying base stations based on 5G

Deployment algorithms of UAV flying base stations based on 5G

Improving photonic Ising machines by way of a stability analysis of steady states

Polynomial Algorithm for Solving Cross-matching Puzzles

Contact Info

Product

Resources

About