works on

From the 1 of 24 linked papers with an AI index.

collaborators

24 papers

cs.DS2026

Online Service with Per-Batch Maximum Delay

Tianhang Lu, Runtian Ren, Shengcai Liu +1

We study online service with one maximum-waiting-time charge per service batch. The persistent server endpoint prevents a phase-by-phase comparison with the offline optimum: an off…

cs.AI2026

Not All Problems Are Best Modeled as MILP: A DSL-Centric Framework for Flexible and Accurate Optimization Modeling

Shaofeng Zhang, Hongyuan Su, Qingwen Peng +4

Solving combinatorial optimization problems (COPs) requires not only efficient algorithms but also carefully crafted formulations. While recent works have leveraged LLMs to automat…

cs.AI2026

Evolving Parallel Algorithm Portfolios via Potential-Aware Instance Generation with LLMs

Shaofeng Zhang, Shengcai Liu, Zhiyuan Wang +1

The Automatic Construction of Portfolios via Large Language Models (LLM-ACP) suffers from poor generalization in practical few-shot scenarios when solving complex combinatorial opt…

cs.NE2026

MuEvo: LLM-Driven Evolution of Multi-Heuristic Ensemble

Haoze Lv, Ning Lu, Shengcai Liu +2

Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optimization problems. However, exi…

cs.AI2026

Cooperative Coevolution for Resource-Constrained Agentic LLM Post-Training

Zhiyuan Wang, Shengcai Liu, Jiahao Wu +5

Tool-using large language model (LLM) agents produce long, multi-turn trajectories, making gradient-based post-training memory-intensive. Evolution strategies (ES) enable memory-ef…

cs.LG2026

Learning-Augmented and Randomized Algorithms for Line Aggregation with Delays

Tianhang Lu, Runtian Ren, Shengcai Liu +1

The paper designs deterministic and randomized online algorithms for line aggregation with delays, incorporating learning-augmented advice and analyzing their robustness, consisten…