most citedGPLight+: A Genetic Programming Method for Learning Symmetric Traffic Signal Control Policy

4 citations · 4 across the 10 of their papers we have counts for

collaborators

15 papers

cs.NE2026

Surrogate-Assisted Genetic Programming with Rank-Based Phenotypic Characterisation for Dynamic Multi-Mode Project Scheduling

Yuan Tian, Yi Mei, Mengjie Zhang

The dynamic multi-mode resource-constrained project scheduling problem (DMRCPSP) is of practical importance, as it requires making real-time decisions under changing project states…

cs.AI2026

Investigation of the Generalisation Ability of Genetic Programming-evolved Scheduling Rules in Dynamic Flexible Job Shop Scheduling

Luyao Zhu, Fangfang Zhang, Yi Mei +1

Dynamic Flexible Job Shop Scheduling (DFJSS) is a complex combinatorial optimisation problem that requires simultaneous machine assignment and operation sequencing decisions in dyn…

cs.AI2026

Scalable Knee-Point Guided Activity Group Selection in Multi-Tree Genetic Programming for Dynamic Multi-Mode Project Scheduling

Yuan Tian, Yi Mei, Mengjie Zhang

The dynamic multi-mode resource-constrained project scheduling problem is a challenging scheduling problem that requires making decisions on both the execution order of activities…

cs.CR2026

Overlooked Safety Vulnerability in LLMs: Malicious Intelligent Optimization Algorithm Request and its Jailbreak

Haoran Gu, Handing Wang, Yi Mei +2

The widespread deployment of large language models (LLMs) has raised growing concerns about their misuse risks and associated safety issues. While prior studies have examined the s…

cs.AI2025

GAMA: A Neural Neighborhood Search Method with Graph-aware Multi-modal Attention for Vehicle Routing Problem

Xiangling Chen, Yi Mei, Mengjie Zhang

Recent advances in neural neighborhood search methods have shown potential in tackling Vehicle Routing Problems (VRPs). However, most existing approaches rely on simplistic state r…

cs.LG2025

SymLight: Exploring Interpretable and Deployable Symbolic Policies for Traffic Signal Control

Xiao-Cheng Liao, Yi Mei, Mengjie Zhang

Deep Reinforcement Learning have achieved significant success in automatically devising effective traffic signal control (TSC) policies. Neural policies, however, tend to be over-p…