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Hysteresis in Combinatorial Optimization Problems
Published 2021-04-01“…Our WCSP framework also allows us to understand hysteresis more generally in combinatorial optimization problems, with or without a connection to physically occurring phenomena.…”
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Robust Combinatorial Optimization with Locally Budgeted Uncertainty
Published 2021-05-01Subjects: Get full text
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Noise Robustness of Quantum Relaxation for Combinatorial Optimization
Published 2024-01-01Subjects: “…Combinatorial optimization…”
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Quantum annealing for combinatorial optimization: a benchmarking study
Published 2025-05-01“…Abstract Quantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods. …”
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Noise-augmented chaotic Ising machines for combinatorial optimization and sampling
Published 2025-01-01“…Abstract Ising machines are hardware accelerators for combinatorial optimization and probabilistic sampling, using stochasticity to explore spin configurations and avoid local minima. …”
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Quick design of feasible tensor networks for constrained combinatorial optimization
Published 2025-07-01“…Particularly, tensor networks have been applied to constrained combinatorial optimization problems for practical applications. …”
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Inductive Construction of Variational Quantum Circuit for Constrained Combinatorial Optimization
Published 2025-01-01Subjects: “…Constrained combinatorial optimization problem…”
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A Quantum Framework for Combinatorial Optimization Problem over Graphs
Published 2025-01-01Subjects: Get full text
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DISCO: Efficient Diffusion Solver for large-scale Combinatorial Optimization problems
Published 2025-09-01Subjects: Get full text
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Automated Pruning Framework for Large Language Models Using Combinatorial Optimization
Published 2025-05-01“…The model pruning problem was modeled as a combinatorial optimization task whose the goal is to minimize model size while maintaining model accuracy. …”
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A Systematic Review on Reinforcement Learning for Industrial Combinatorial Optimization Problems
Published 2025-01-01Subjects: “…combinatorial optimization…”
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Earthquake Recurrence Estimates for Northern Caribbean Faults from Combinatorial Optimization
Published 2025-01-01“…We use combinatorial optimization to find the optimal spatial distribution of random samples of earthquakes (≥6.5) that minimize the misfit in target slip rates for all faults in the northeast Caribbean, and we derive magnitude–frequency relationships with uncertainties for these faults. …”
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Multi-scenario Load Combinatorial Optimization Based on Improved Greedy Algorithm
Published 2020-05-01Subjects: Get full text
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Quantum-Inspired Genetic Algorithm Based on Simulated Annealing for Combinatorial Optimization Problem
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AutoRL-Sim: Automated Reinforcement Learning Simulator for Combinatorial Optimization Problems
Published 2024-08-01“…In this context, this work aims to propose a simulation environment for combinatorial optimization problems using AutoRL. The AutoRL-Sim includes several experimentation modules that cover studies on the symmetric traveling salesman problem, the asymmetric traveling salesman problem, and the sequential ordering problem. …”
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Short Paper - A Note on Robust Combinatorial Optimization with Generalized Interval Uncertainty
Published 2023-06-01Subjects: “…robust combinatorial optimization…”
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An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems
Published 2025-04-01“…Additionally, EDO-LFOL is tested on three combinatorial optimization challenges: the job shop scheduling problem (JSSP), quadratic assignment problem (QAP), and bin packing problem (BPP), to evaluate its applicability. …”
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ADVCSO: Adaptive Dynamically Enhanced Variant of Chicken Swarm Optimization for Combinatorial Optimization Problems
Published 2025-05-01“…The proposed algorithm demonstrates an exceptional performance in combinatorial optimization and holds a significant engineering application value.…”
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Numerical Analysis of Digital Twin System Modeling Methods Aided by Graph-Theoretic Combinatorial Optimization
Published 2022-01-01“…This paper combines the digital twin system modeling method to conduct an in-depth study and analysis of graph-theoretic combinatorial optimization. This paper provides new ideas and approaches for optimal numerical analysis work by studying the digital twin modeling method that integrates digital modeling and graph theory combination, provides theoretical support for safe, stable, and economic operation of the system, proposes a solution for digital twin model based on big data platform, focuses on the nearest neighbor propagation (AP) and graph theory combination, solves the digital twin real-time monitoring data asynchronous, incomplete problem, and applies the algorithm to the digital twin model based on the big data platform for data preprocessing to achieve better results. …”
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