- Autoregressive RL Approach for Mixed-Integer Linear Programs.- Algorithm Configuration in the Unified Planning Framework.- Learning to Repair Infeasible$^*$ Problems with Deep Reinforcement Learning on Graphs.- Optimal Matched Block Design For Multi-Arm Experiments.- CHORUS: Zero-shot Hierarchical Retrieval and Orchestration for Generating Linear Programming Code.- Taxi re-positioning considering driver compliance.- A Shared Memory Optimal Parallel Redistribution Algorithm for SMC Samplers with Variable Size Samples.- A Hybrid Quantum-Inspired and Deep Learning Approach for the Capacitated Vehicle Routing Problem with Time Windows.

- Multi-Action Sampling with Deep Reinforcement Learning for Traveling Salesman Problem.- Adaptive Bias Generalized Rollout Policy Adaptation on the Flexible Job-Shop Scheduling Problem.- Codetector: A Framework for Zero-shot Detection of AI-Generated Code.- Pushing the Limits of the Reactive Affine Shaker Algorithm to Higher Dimensions.- Convex quadratic programming-based predictors: An algorithmic framework and a study of possibilities and computational challenges.- Studies on a Bayesian Optimization Based Approach to Tune Hyperparameters of Matheuristics.- Local iterative algorithms for approximate symmetry guided by network centralities.- Addressing Over-fitting in Passive Constraint Acquisition through Active Learning.

- Learning to solve the Skill Vehicle Routing Problem with Deep Reinforcement Learning.- CGD: Modifying the Loss Landscape by Gradient Regularization.- Data Sampling-driven Adaptive Modification of Bus Routes Under Time-Varying Road Conditions.