@article{Hà2026,

title = {On the Hierarchical Directed Capacitated Arc Routing Problem},

author = {Minh Hoàng Hà and Thu Huong Dang and Ba Luat Le and Trung Thanh Nguyen and André Langevin},

doi = {10.1016/j.cor.2026.107495},

issn = {0305-0548},

year  = {2026},

date = {2026-08-01},

journal = {Computers & Operations Research},

volume = {192},

publisher = {Elsevier BV},

keywords = {DATAOPT Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Beyond Homogeneous Adversaries: Stackelberg Security Games with Mixed Quantal Response},

author = {Hoang Giang Pham, Tien Mai, Thuy Anh Ta, Minh Hoàng Hà},

year  = {2026},

date = {2026-07-31},

abstract = {The quantal response (QR) model is widely used in Stackelberg security games (SSGs) to capture boundedly rational adversaries. Existing work on SSGs under QR, however, almost exclusively assumes a homogeneous attacker population, ignoring heterogeneity in attacker preferences and rationality. We study SSG with mixed quantal response attackers, where the follower population consists of multiple discrete attacker types, each following a type-specific QR model. The defender allocates limited resources across targets, while an attacker drawn from this heterogeneous population observes the defender’s strategy and attacks a single target. This results in a highly non-convex equilibrium computation problem. We develop a polynomial-time approximation scheme (PTAS) for this setting when the number of attacker types is bounded, based on an exponential cone programming formulation combined with a carefully designed Branch-and-Bound procedure. Experiments demonstrate that our approach outperforms standard gradient-based methods and that explicitly modeling attacker heterogeneity yields significant gains over traditional SSG models with a single QR attacker.},

keywords = {CADA Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Le2026,

title = {Competitive Facility Location Under Cross-Nested Logit Customer Choice Model: Hardness and Exact Approaches},

author = {Ba Luat Le and Tien Mai and Thuy Anh Ta and Minh Hoàng Hà and Duc-Minh Vu},

doi = {10.1287/ijoc.2025.1150},

issn = {1526-5528},

year  = {2026},

date = {2026-05-06},

urldate = {2026-05-06},

journal = {INFORMS Journal on Computing},

publisher = {Institute for Operations Research and the Management Sciences (INFORMS)},

abstract = {<jats:p>We study the competitive facility location problem, in which a firm aims to establish new facilities in a market already occupied by competitors. In this problem, customer behavior is a crucial factor in making optimal location decisions. We explore a general class of customer choice models, known as the cross-nested logit model, which is recognized for its flexibility and generality in predicting people’s choice behavior. To explore the problem, we first demonstrate that it is NP-hard even when there is only one customer class and the cross-nested structure has only two nests. To tackle the challenging facility location problem, we demonstrate that the objective function under a general cross-nested structure is not concave. Interestingly, we show that, by a change of variables, the objective function can be converted to a mixed-integer exponential cone convex program, enabling it to be solved to optimality via an outer approximation algorithm. Extensive experiments show the efficiency of our approach and provide analyses on the benefits of using the cross-nested model in the facility location context.</jats:p>

                  <jats:p>History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms–Discrete.</jats:p>

                  <jats:p>Funding: This work was supported by the Vingroup Innovation Foundation, Vietnam [Grant VINIF.2024.DA072].</jats:p>

                  <jats:p>Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1150 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1150 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .</jats:p>},

keywords = {CADA Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Dang2026WaterLevelAutoencoder,

title = {An Autoencoder Approach to Water Level Forecasting},

author = {T. L. Dang and K. -N. T. Nguyen and N. Q. Dinh and D. Nguyen-Ngoc},

doi = {10.51316/jst.187.ssad.2026.36.1.9},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {Journal of Science and Technology - Smart Systems and Devices},

volume = {36},

number = {1},

pages = {071–079},

keywords = {BUSINESS AI Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Vu2026DemandResponseReview,

title = {Designing effective demand response: A review of behavioral insights, consumer engagement, and operational strategies in energy systems},

author = {Duc D. Vu and Akhtar Hussain and Duc-Minh Vu and Xiao Zhang and Van-Hai Bui},

doi = {10.1016/j.erss.2025.104474},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {Energy Research & Social Science},

volume = {131},

pages = {104474},

publisher = {Elsevier},

keywords = {SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{rosati2026_conflicting_jobs_itor,

title = {Exact and Metaheuristic Approaches to Minimizing Makespan in Parallel Machine Scheduling with Conflicting Jobs},

author = {Roberto Maria Rosati and Dinh Quy Ta and Minh Hoang Ha and Andrea Schaerf},

doi = {10.1111/itor.70177},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {International Transactions in Operational Research},

pages = {1–27},

note = {Version of record online: 15 February 2026},

keywords = {CADA Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Le2026CFL_CNL,

title = {Competitive Facility Location under Cross-Nested Logit Customer Choice Model: Hardness and Exact Approaches},

author = {Ba Luat Le and Tien Mai and Thuy Anh Ta and Minh Hoang Ha and Duc Minh Vu},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {INFORMS Journal on Computing},

note = {Accepted March 2026, to appear},

keywords = {CADA Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Ulziisaikhan2026Band2CleanFormer,

title = {Band2CleanFormer: Integrating band-specific processing and inter-band attention for robust EEG denoising},

author = {B. Ulziisaikhan and T. -N. Nguyen and S. -H. Kim},

doi = {10.1016/j.bspc.2026.109860},

issn = {1746-8094},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {Biomedical Signal Processing and Control},

volume = {119},

pages = {109860},

keywords = {BUSINESS AI Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Vu2025CountingTraffic,

title = {Counting Mixed Traffic Volumes at Motorcycle-Dominated Intersections by Using Computer Vision},

author = {Tam Vu and Hong Nam Thai and Viet Ngoc Pham and Huy Tuan Vu and Anh Tuan Luong and Thien Van Luong},

url = {https://doi.org/10.1007/s13177-024-00442-z},

doi = {10.1007/s13177-024-00442-z},

year  = {2025},

date = {2025-04-01},

urldate = {2025-04-01},

journal = {International Journal of Intelligent Transportation Systems Research},

volume = {23},

number = {1},

pages = {146–164},

keywords = {BUSINESS AI Lab},

pubstate = {published},

tppubtype = {article}

}

@article{zhao2025_irp_hgs,

title = {Large Neighborhood and Hybrid Genetic Search for Inventory Routing Problems},

author = {Jingyi Zhao and Claudia Archetti and Tuan Anh Pham and Thibaut Vidal},

doi = {10.1016/j.ejor.2025.11.021},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {European Journal of Operational Research},

note = {In press, corrected proof; available online 25 November 2025},

keywords = {CADA Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{thieu2025_metaperceptron,

title = {MetaPerceptron: A Standardized Framework for Metaheuristic-Driven Multi-Layer Perceptron Optimization},

author = {Nguyen Van Thieu and Seyedali Mirjalili and Harish Garg and Nguyen Thanh Hoang},

doi = {10.1016/j.csi.2025.103977},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Computer Standards & Interfaces},

volume = {93},

pages = {103977},

keywords = {SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{thieu2025_graforvfl,

title = {GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network},

author = {Nguyen Van Thieu and Nguyen Thanh Hoang and Hossam Faris},

doi = {10.1016/j.neucom.2025.130898},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Neurocomputing},

volume = {651},

pages = {130898},

keywords = {SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}

@article{Luong2025OTFSDeepLearning,

title = {Deep learning for noncoherent OTFS modulation},

author = {T. V. Luong and V. -C. Pham},

doi = {10.1007/s11235-025-01312-z},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Telecommunication Systems},

volume = {88},

number = {2},

pages = {73–90},

keywords = {BUSINESS AI Lab},

pubstate = {published},

tppubtype = {article}

}

@article{nguyen2025_stop,

title = {The Set Team Orienteering Problem},

author = {Tat Dat Nguyen and Rafael Martinelli and Quang Anh Pham and Minh Hoang Ha},

doi = {10.1016/j.ejor.2024.09.021},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {European Journal of Operational Research},

volume = {321},

number = {1},

pages = {75–87},

keywords = {CADA Lab, SLSCM Lab},

pubstate = {published},

tppubtype = {article}

}