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20192026
most citedHybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers

36 citations · 131 across the 21 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.AI2023

A Quantum Computing-based System for Portfolio Optimization using Future Asset Values and Automatic Reduction of the Investment Universe

Eneko Osaba, Guillaume Gelabert, Esther Villar-Rodriguez +2

One of the problems in quantitative finance that has received the most attention is the portfolio optimization problem. Regarding its solving, this problem has been approached usin…

quant-ph2023★ 8 cited

Optimization of Image Acquisition for Earth Observation Satellites via Quantum Computing

Antón Makarov, Márcio M. Taddei, Eneko Osaba +3

Satellite image acquisition scheduling is a problem that is omnipresent in the earth observation field; its goal is to find the optimal subset of images to be taken during a given…

quant-ph2023★ 15 cited

Digital-Analog Quantum Computation with Arbitrary Two-Body Hamiltonians

Mikel Garcia-de-Andoin, Álvaro Saiz, Pedro Pérez-Fernández +3

Digital-analog quantum computing is a computational paradigm which employs an analog Hamiltonian resource together with single-qubit gates to reach universality. Here, we design a…

quant-ph2023★ 2 cited

Formulation of the Electric Vehicle Charging and Routing Problem for a Hybrid Quantum-Classical Search Space Reduction Heuristic

M. Garcia de Andoin, A. Bottarelli, S. Schmitt +3

Combinatorial optimization problems have attracted much interest in the quantum computing community in the recent years as a potential testbed to showcase quantum advantage. In thi…

cs.ET2023★ 36 cited

Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers

Sebastián V. Romero, Eneko Osaba, Esther Villar-Rodriguez +2

Efficient packing of items into bins is a common daily task. Known as Bin Packing Problem, it has been intensively studied in the field of artificial intelligence, thanks to the wi…