2 citations · 7 across the 14 of their papers we have counts for
10 papers · 1 filter
Beyond Average Performance: Dynamic Instance Clustering and Specialized Algorithm Design in LLM-Assisted Evolutionary Search
Qinglong Hu, Qingfu Zhang, Fei Liu +3
Large Language Model-assisted Evolutionary Search (LES) has emerged as a powerful paradigm for automated algorithm design. However, existing LES methods primarily optimize for aver…
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…
Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver
Changliang Zhou, Xi Lin, Zhenkun Wang +3
In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial. It presents unique challenges driven…
Enhancing CVRP Solver through LLM-driven Automatic Heuristic Design
Zhuoliang Xie, Fei Liu, Zhenkun Wang +1
The Capacitated Vehicle Routing Problem (CVRP), a fundamental combinatorial optimization challenge, focuses on optimizing fleet operations under vehicle capacity constraints. While…
Learning to Reduce Search Space for Generalizable Neural Routing Solver
Changliang Zhou, Xi Lin, Zhenkun Wang +1
Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to construct approximate optimal s…
LLM4AD: A Platform for Algorithm Design with Large Language Model
Fei Liu, Rui Zhang, Zhuoliang Xie +10
We introduce LLM4AD, a unified Python platform for algorithm design (AD) with large language models (LLMs). LLM4AD is a generic framework with modularized blocks for search methods…