Wei-Hua Bai

A guided-ejection memetic algorithm for the three-objective VRPTW: Fleet, distance and workload balance

The vehicle routing problem with time windows (VRPTW) underpins distribution and field-service operations, yet most multi-objective treatments optimise only fleet size and travelled distance, and rely on generic evolutionary operators that struggle to move the discrete, rugged fleet-size axis. We study a three-objectiv...

SpectralMol: Spectral Graph Bisection Achieves Universal Molecular Fragment Decomposition for Drug-Like Molecule Generation

Generating valid, diverse, and drug-like molecules remains a central challenge in computational drug discovery. A key bottleneck for fragment-based generative models is decomposition coverage: existing junction-tree methods fail on bridged bicyclic and spiro ring systems common in drug-like scaffolds. Our primary con...

: Spectral Graph Bisection Achieves Universal Molecular Fragment Decomposition for Drug-Like Molecule Generation

CausalSTKT: Disentangled Spatiotemporal Heterogeneous Graph Learning for Robust Knowledge Tracing Under Distribution Shifts

CausalSTKT is proposed, an SCM-guided knowledge tracing framework that integrates spatiotemporal modeling over a global item–knowledge-component bipartite graph with disentangled representation learning and derives an out-of-distribution risk bound showing that a smaller representation-entanglement residual leads to a...

Causal Benefit-Aware Recommendation for Personalized Learning-Path Features: A Targeting-Policy Framework with Provable Guarantees and Randomized Evaluation

This work formalizes feature recommendation as a causal targeting-policy problem: rank students by the estimated conditional average treatment effect (CATE) of a feature and recommend to the top of the ranking, proving causal top-CATE targeting maximizes policy value at any budget and weakly dominates predictive (outco...

VulGNN: A high-fidelity graph neural network framework for robust smart contract vulnerability detection