Results 31 to 40 of about 10,333,076 (321)

On a combination of the 1-2-3 Conjecture and the Antimagic Labelling Conjecture [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2017
This paper is dedicated to studying the following question: Is it always possible to injectively assign the weights 1, ..., |E(G)| to the edges of any given graph G (with no component isomorphic to K2) so that every two adjacent vertices of G get ...
Julien Bensmail   +2 more
doaj   +1 more source

On locally irregular decompositions and the 1-2 Conjecture in digraphs [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2018
The 1-2 Conjecture raised by Przybylo and Wozniak in 2010 asserts that every undirected graph admits a 2-total-weighting such that the sums of weights "incident" to the vertices yield a proper vertex-colouring.
Olivier Baudon   +3 more
doaj   +1 more source

Approximation Algorithms

open access: yesInternational Symposium on Parallel Architectures, Algorithms and Networks, 2021
Description This course deals with the design and analysis of algorithms for combinatorial optimization problems such as graph problems (matchings, network design, covering problems), scheduling and packing problems.
Mohit Singh, K. Talwar
semanticscholar   +1 more source

A general decomposition theory for the 1-2-3 Conjecture and locally irregular decompositions [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2019
How can one distinguish the adjacent vertices of a graph through an edge-weighting? In the last decades, this question has been attracting increasing attention, which resulted in the active field of distinguishing labellings.
Olivier Baudon   +7 more
doaj   +1 more source

Meta-heuristic algorithms in car engine design: a literature survey [PDF]

open access: yes, 2015
Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy.
Tayarani-N, Mohammad-H.   +2 more
core   +2 more sources

Limitations of optimization algorithms on noisy quantum devices [PDF]

open access: yesNature Physics, 2020
Recent successes in producing intermediate-scale quantum devices have focused interest on establishing whether near-term devices could outperform classical computers for practical applications.
Daniel Stilck França   +1 more
semanticscholar   +1 more source

The Arithmetic Optimization Algorithm

open access: yesComputer Methods in Applied Mechanics and Engineering, 2021
Este trabajo propone un nuevo método metaheurístico llamado Algoritmo de Optimización Aritmética (AOA) que utiliza el comportamiento de distribución de los principales operadores aritméticos en matemáticas, incluyendo (Multiplicación (M), División (D), Resta (S) y Suma (A)).
Laith Abualigah   +4 more
openaire   +2 more sources

Algorithmic GPGPU memory optimization [PDF]

open access: yes2013 International SoC Design Conference (ISOCC), 2013
The performance of General-Purpose computation on Graphics Processing Units (GPGPU) is heavily dependent on the memory access behavior. In this paper, we present an algorithmic methodology to semi-automatically find the best mapping of memory accesses present in serial loop nest to underlying data-parallel architectures based on a comprehensive static ...
Byunghyun Jang, Minsu Choi, Kyung Ki Kim
openaire   +1 more source

A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments [PDF]

open access: yes, 2019
In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance.
Fayaz, Muhammad   +4 more
core   +2 more sources

Optimization of machine learning algorithms for proteomic analysis using topsis

open access: yesЖурнал інженерних наук, 2022
The present study focuses on a new application of the TOPSIS method for the optimization of machine learning algorithms, supervised neural networks (SNN), the quick classifier (QC), and genetic algorithm (GA) for proteomic analysis.
Javanbakht T., Chakravorty S.
doaj   +1 more source

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