Cover Image

An Amortized Efficiency Threshold for Comparing Neural and Heuristic Solvers in Combinatorial Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Afifi, Sohaib
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization
by: Wang, Rongzheng, et al.
Published: (2026)

Small Contributions, Small Networks: Efficient Neural Network Pruning Based on Relative Importance
by: Hussien, Mostafa, et al.
Published: (2024)

Learning to Reduce Search Space for Generalizable Neural Routing Solver
by: Zhou, Changliang, et al.
Published: (2025)

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver
by: Zhou, Changliang, et al.
Published: (2024)

Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization
by: Tao, Peng, et al.
Published: (2024)

Optimizing PM2.5 Forecasting Accuracy with Hybrid Meta-Heuristic and Machine Learning Models
by: Ghafariasl, Parviz, et al.
Published: (2024)

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization
by: Li, Xingyu
Published: (2026)

Heuristically Adaptive Diffusion-Model Evolutionary Strategy
by: Hartl, Benedikt, et al.
Published: (2024)

Survey on Neural Routing Solvers
by: Ba, Yunpeng, et al.
Published: (2026)

Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learning
by: Holliday, Andrew, et al.
Published: (2024)

Izhikevich-Inspired Temporal Dynamics for Enhancing Privacy, Efficiency, and Transferability in Spiking Neural Networks
by: Moshruba, Ayana, et al.
Published: (2025)

Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations
by: Tripp, Charles Edison, et al.
Published: (2024)

A Generative Neural Annealer for Black-Box Combinatorial Optimization
by: Zhang, Yuan-Hang, et al.
Published: (2025)

The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning
by: Nguyen, Manh V., et al.
Published: (2024)

Benchmarking Randomized Optimization Algorithms on Binary, Permutation, and Combinatorial Problem Landscapes
by: Odeyemi, Jethro, et al.
Published: (2025)

Cascaded Transformer for Robust and Scalable SLA Decomposition via Amortized Optimization
by: Hsu, Cyril Shih-Huan
Published: (2026)

Multi-scale Topology Optimization using Neural Networks
by: Chen, Hongrui, et al.
Published: (2024)

Neural Architecture Search using Particle Swarm and Ant Colony Optimization
by: Lankford, Séamus, et al.
Published: (2024)

Closing the gap: Optimizing Guidance and Control Networks through Neural ODEs
by: Origer, Sebastien, et al.
Published: (2024)

Pareto-Grid-Guided Large Language Models for Fast and High-Quality Heuristics Design in Multi-Objective Combinatorial Optimization
by: Ha, Minh Hieu, et al.
Published: (2025)

Active Learning for Neural PDE Solvers
by: Musekamp, Daniel, et al.
Published: (2024)

TrajEvo: Trajectory Prediction Heuristics Design via LLM-driven Evolution
by: Zhao, Zhikai, et al.
Published: (2025)

Sensitivity-Aware Mixed-Precision Quantization and Width Optimization of Deep Neural Networks Through Cluster-Based Tree-Structured Parzen Estimation
by: Azizi, Seyedarmin, et al.
Published: (2023)

Enabling Population-Based Architectures for Neural Combinatorial Optimization
by: Garmendia, Andoni Irazusta, et al.
Published: (2026)

Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks
by: Mazandarani, Mehran, et al.
Published: (2025)

Neural Interpretable Reasoning
by: Barbiero, Pietro, et al.
Published: (2025)

Probabilistic Neural Circuits
by: Martires, Pedro Zuidberg Dos
Published: (2024)

LLS: Local Learning Rule for Deep Neural Networks Inspired by Neural Activity Synchronization
by: Apolinario, Marco Paul E., et al.
Published: (2024)

Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
by: Bal, Melis Ilayda, et al.
Published: (2024)

Causal Learning with Neural Assemblies
by: Kopadi, Evangelia, et al.
Published: (2026)

Deep Neural Regression Collapse
by: Rangamani, Akshay, et al.
Published: (2026)

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization
by: Gu, Shengda, et al.
Published: (2025)

Restricted Bayesian Neural Network
by: Ganguly, Sourav, et al.
Published: (2024)

Polysemanticity and Capacity in Neural Networks
by: Scherlis, Adam, et al.
Published: (2022)

Deep Oscillatory Neural Network
by: Rohan, Nurani Rajagopal, et al.
Published: (2024)

Time Elastic Neural Networks
by: Marteau, Pierre-François
Published: (2024)

Sheaf Neural Networks and biomedical applications
by: Mehrab, Aneeqa, et al.
Published: (2026)

Spark: Modular Spiking Neural Networks
by: Franco, Mario, et al.
Published: (2026)

Explainable Benchmarking for Iterative Optimization Heuristics
by: van Stein, Niki, et al.
Published: (2024)

Continuous Spiking Graph Neural Networks
by: Yin, Nan, et al.
Published: (2024)