From the 1 of 6 linked papers with an AI index.
6 papers
Don't Regenerate, Debug: A Domain-Specific Agent for Repairing Near-Miss Hardware Operators
Yansong Sun, Shenxiu Wu, Siyuan Chen +6
Kernel generation for hardware accelerators such as GPUs and NPUs has become a proving ground for large language models (LLMs), and state-of-the-art systems raise correctness throu…
AgenticCANN: Automated Ascend C Operator Generation via Knowledge-Augmented Agentic Evolution
Junhao Qiu, Zidong Wang, Yansong Sun +3
The paper introduces AgenticCANN, a framework that uses large language models combined with knowledge‑augmented, stage‑adaptive agents to automatically generate and optimize Ascend…
A Sliding-Window-Based Reinforcement Learning for Dynamic Assembly Flow Shop Scheduling with Multi-Product Delivery
Junhao Qiu, Jianjun Liu, Ting Liu +3
Multi-product kitting delivery imposes significant challenges for real-time scheduling in hybrid manufacturing systems that integrate processing and assembly, as dynamic order arri…
EvoDR: Evolving Dispatching Rules via Large Language Model for Dynamic Flexible Assembly Flow Shop Scheduling
Junhao Qiu, Haoyang Zhuang, Fei Liu +2
Dynamic flexible assembly flow shop scheduling with multi-product delivery is a critical combinatorial problem, characterized by kitting supply and machine flexibility. Genetic pro…
Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
Junhao Qiu, Xin Chen, Liang Ge +3
Neighborhood search operators are critical to the performance of Multi-Objective Evolutionary Algorithms (MOEAs) and rely heavily on expert design. Although recent LLM-based Automa…
Online Operator Design in Evolutionary Optimization for Flexible Job Shop Scheduling via Large Language Models
Rongjie Liao, Junhao Qiu, Xin Chen +1
Customized static operator design has enabled widespread application of Evolutionary Algorithms (EAs), but their search effectiveness often deteriorates as evolutionary progresses.…