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From the 1 of 12 linked papers with an AI index.

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20242026
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12 papers

quant-ph2026

Quantum-Informed Portfolio Selection: An End-to-End Pipeline Validated on Trapped-Ion Hardware with Real Market Data

Romina Yalovetzky, Martin J. A. Schuetz, Zichang He +11

The paper presents a hybrid quantum‑classical pipeline (qReduMIS) that uses QAOA measurements to guide reductions for solving portfolio diversification formulated as a Maximum Inde…

quant-ph2026

qReduMIS: A Quantum-Informed Reduction Algorithm for the Maximum Independent Set Problem

Martin J. A. Schuetz, Romina Yalovetzky, Ruben S. Andrist +8

We propose and implement a quantum-informed reduction algorithm for the maximum independent set problem that integrates classical kernelization techniques with information extracte…

math.OC2026

Applying a Random-Key Optimizer on Mixed Integer Programs

Antonio A. Chaves, Mauricio G. C. Resende, Carise E. Schmidt +3

Mixed-Integer Programs (MIPs) are NP-hard optimization models that arise in a broad range of decision-making applications, including finance, logistics, energy systems, and network…

quant-ph2025

Direct comparison of stochastic driven nonlinear dynamical systems for combinatorial optimization

Junpeng Hou, Amin Barzegar, Helmut G. Katzgraber

Combinatorial optimization problems are ubiquitous in industrial applications. However, finding optimal or close-to-optimal solutions can often be extremely hard. Because some of t…

quant-ph2025

Quantum-Guided Cluster Algorithms for Combinatorial Optimization

Peter J. Eder, Aron Kerschbaumer, Jernej Rudi Finžgar +5

Finding the ground state of Ising spin glasses is notoriously difficult due to disorder and frustration. Often, this challenge is framed as a combinatorial optimization problem, fo…

cs.AI2025

A Random-Key Optimizer for Combinatorial Optimization

Antonio A. Chaves, Mauricio G. C. Resende, Martin J. A. Schuetz +4

This paper introduces the Random-Key Optimizer (RKO), a versatile and efficient stochastic local search method tailored for combinatorial optimization problems. Using the random-ke…