Home » AI Researchs » Research Team » Optimization

Introduction

In our daily lives, we benefit from the application of Optimization theories and algorithms. They are used, for example, by IoT devices, GPS systems, by shipping companies delivering packages to our homes, by financial companies, airline reservations systems, etc. Optimization is a discipline that solves a great variety of real-world applied problems in diverse areas: transportation, supply chain, manufacturing, finance, government, economics, etc.

Our research group consists of academic staffs in the School of Information and Technology (SoICT) who are actively involved in teaching, supervising and researching across a wide range of topics and areas in Optimization. Our research focuses on the development, analysis and implementation of advanced theories and algorithms to provide high value solutions to complex real-world problems and challenges. We also have research collaboration with other optimization groups of Nanyang Technological University, Singapore Management University (Singapore) and University of Sydney, La Trobe University, University of Technology Sydney (Australia).

See the slides here for more detail.

Contact: Assoc. Prof. Huynh Thi Thanh Binh, Email: binhht@soict.hust.edu.vn

Research Directions

  • Logistics and transportation optimization: Transportation is a very relevant sector for contemporary society, both for companies and individuals. Every day, thousands types of commodities such as fresh food, frozen or dairy products, small to large packages, etc. are shipped between locations within or outside cities.Thanks to the development of digitization and automation technologies, in the past few years, we have seen an increase in the number of logistics companies. Their main goal is to transport different kinds of goods domestically and internationally based on customer needs. They thus all share the same challenges: how to manage limited fleets of vehicles, handle warehouses, mange inventory, etc. to make profit as much as possible, while enhancing customer satisfaction, improving working conditions for drivers, reduce carbon footprint, etc. Given these presence of multiple business constraints, our research is to analyze, design and develop planning and optimization methods to create better decision support to companies within the supply chains, transport sector.
  • Multitask learning, transfer learning: Inspired by the human solving ability that routinely uses a pool of knowledge drawn from past experiences whenever faced with a new task, Transfer Learning and Multitask Learning have gained much attention within the Artificial Intelligence community. Besides, real-world problems seldom exist in isolation. For example, many routing problems are repetitive or and network designs share common characteristics or support each other. Knowledge from solving one problem may help solve other problems more efficiently. Transfer Learning aims at solving problems that occur sequentially, and the knowledge obtained when tackling preceding tasks is employed as external information when dealing with new problems/instances. In contrast, Multitasking Learning tackles multiple different tasks simultaneously by dynamically online exploiting synergies existing among them. Viewed from different angles, Transfer Learning and Multitask Learning can be applied to various optimization fields, ranging from theory to practice. Our work focuses on designing novel multitasking algorithms that can simultaneously solve a massive number of tasks. Besides, we will investigate these approaches to solve real-world optimization problems.
  • Multi-domain network design optimization: A multi-domain network consists of multiple domains, in which each domain is administrated as a unit with the same rules and procedures. Routing is the fundamental problem showing the path of resources in the network. In a communication network, efficient routing provides more control to the operators and enables the delivery of services with quality of service across domain boundaries. In Military communication, various elements of military forces, such as the army, navy, air forces, and special units, cooperate to achieve specific tactical goals. Each one of these organizations has its network structure in one or more domains. Besides, freight routing planning aims at assigning optimal routes to move commodities from their origins to the respective destinations through the transportation networks. Although it is a short-term decision making in the transportation network design, freight routing planning is oriented directly on satisfying the customers’ demand, and its performance determines the competitiveness of a transportation carrier or a third-party logistics company in the freight market.
  • Charging schedule optimization in Wireless Rechargeable Sensor Networks: Sensor nodes in conventional Wireless Sensor Networks are often powered by batteries, thus, they can only operate for a limited period of time depending on battery capacities. When some sensors deplete their energy, the network would become fragmented and the data from some parts of the sensing field can no longer be extracted. Wireless energy charging was proposed as a promising technique to address the energy provisioning problem. However, this technology also brings new challenges, including charging scheduling and energy forecasting for constructing an effective charging schedule. Solving these problems is of great significance, as the first step to exploiting the wireless charging technology and providing sustainable power for sensor networks. It can be applied in the harshness of environments, such as earthquakes, soil monitoring, large scale wireless sensor networks.
  • Path planning with energy optimization for mobile robots: Mobile robots have become more commonplace in commercial and industrial settings. Hospitals have been using autonomous mobile robots to transfer materials. Warehouses have installed mobile robotic systems to efficiently move materials from stocking shelves to order fulfillment zones. Mobile robots are also found in industrial, military and security settings. To power a mobile robot usually use batteries. Battery power is limited. In order for the robot to work effectively, it is necessary to schedule the optimal robot path to optimize energy; need to predict exhausted energy to plan charging in time.
  • Optimization techniques for Credit scoring problem: Credit scores are the most commonly used tool by financial institutions for determining consumer credit risk. In the last few decades, quantitative methods known as credit scoring models have been developed for the credit granting decision. The objective of quantitative credit scoring models is to assign credit applicants to one of two groups: a “good credit” group that is likely to repay the financial obligation, or a “bad credit” group that should be denied credit because of a high likelihood of defaulting on the financial obligation. However, quantitative methods have some limitations, such as they can not consider additionally constraints defined by risk management experts, they base completely on training dataset. This leads to our research direction, how to apply optimization techniques to build credit scoring models (non-parametric approaches), which not only are more accurate, but also can consider side constraints defined by users. Potential optimization techniques in this research are both complete search approaches (Integer Programming, Constraint Programming) and incomplete search approaches (Local Search, Meta-Heursitic).
  • Resources management in the cloud-fog environment optimization: In recent years, the Internet of Things (IoT) has been one of the most popular technologies that facilitate new interactions among things and humans to enhance the quality of life. With the rapid development of IoT applications, fog computing is an emerging distributed computing paradigm that has recently attracted the attention of both the industry and academic community for guaranteeing the requests of computational applications in IoT smart devices. In the fog environment, IoT applications are executed by the intermediate computing nodes in the fog, as well as the physical servers in cloud data centers. Fog computing contributes to processing large amounts of data generated in smart transportation, smart grid, smart health, smart home, and smart home, and other latency-sensitive applications. On the other hand, due to the resource limitations, resource heterogeneity, dynamic nature, and unpredictability of the fog environment, it necessitates resource management issues as one of the challenging problems to be considered in the fog landscape. To solve the resource management challenge, we adopt several promising approaches such as heuristics, deep learning, reinforcement learning, …
  • Graph Neural Network for combinatorial optimization: Combinatorial optimization (CO) aims to find optimal configurations in discrete spaces where exhaustive enumeration is intractable. In general, the CO problems can be divided into three subclasses: Mixed Integer Program (MIP), Satisfiability Problem (SAT), and Constraint Program (CP). Many real world problems with high applicability can be formulated as CO problems, especially MIP problems such as Traveling Salesman Problem, Set Covering, Maximal Independent Set, etc. Current SOTA CO solvers often use sophisticated heuristics to solve hard CO problems. However, these solvers will try to solve the new issue from scratch without utilizing knowledge from previous problems. On the other hand, most CO problems have many common elements. So can we take advantage of the common ground between these problems? Obviously, machine learning can! We formulate CO problems with graph representation and use the Graph Neural Network to approximate the distribution of each CO problem. This can support traditional algorithms, speeding up the solving time with a data-driven approach.
  • Maximizing Wireless Sensor Network Coverage: Coverage which is one of the most important performance metrics for sensor networks reflects how well a sensor field is monitored. Individual sensor coverage models are dependent on the sensing functions of different types of sensors, while network-wide sensing coverage is a collective performance measure for geographically distributed sensor nodes. A major problem when designing these networks is deploying sensors such that their area coverage is maximized. Given a number of sensors with heterogeneous sensing ranges, the problem of coverage maximization is known to be NP-hard. As such, our main goal is to analyze and develop novel methods that rely on metaheuristic algorithms to support sensor network design/deployment with realistic requirements.

Research Problems

  • Optimization in the transportation, drone problems: Research optimization algorithms in the Trucks and Drones delivery problem, Door to Door sampling services, Multi-echelon distribution system in city logistics; Transportation Logistics Networks; minimum routing cost problems in the multi-domain networks;
  • Multi-objective optimization, multi-tasking evolutionary algorithms: Research and application of multi-objective, multi-tasking evolutionary algorithms in solving interdisciplinary optimization problems.
  • Multi-domain network design optimization: Develop multitasking evolutionary and heuristic algorithms to find the shortest path with uniqueness constraints and efficient network structures in the multi-domain network.
  • Charging schedule optimization:study wireless charging models to prolong the life of the network; Propose algorithms to optimize the cycle of the charging robot, optimize the charging stop time; energy prediction to plan charging on time.
  • Path planning with energy optimization for mobile robots: Propose optimization algorithms to find shortest path, minimizing energy for mobile robots; predict energy to plan charging in time.
  • Optimization techniques for Credit scoring problem: Study optimization techniques – complete search approaches (Integer Programming, Constraint Programming) and incomplete search approaches (Local Search, Meta-Heursitic) to solve credit score problem.
  • Reinforcement Learning for Combinatorial Optimization: Design Reinforcement Learning frameworks to solve complex combinatorial optimization instead of using traditional optimization algorithms.
  • Resources management in the cloud-fog environment optimization: Propose heuristics, deep learning, reinforcement learning to solve resources management in fog computing.

Team Members

Assoc. Prof. Huynh Thi Thanh Binh
Team Leader

Assoc. Prof. Do Phan Thuan
Member

Dr. Pham Quang Dung
Member

Dr. Do Tien Dung
Member

Dr. Nguyen Khanh Phuong
Member

Dr. Ban Ha Bang
Member

Dr. Bui Quoc Trung
Member

Post-doc and PhD students

Do Tuan Anh
PhD Student

Tran Thi Huong
PhD Student

Do Bao Son
PhD Student

Nguyen Van Son
PhD Student

Nguyen Thi Tam
POST-DOC

Dr. Nguyen Thi Hanh
Post-doc

Dr. Hoang Thi Diep
Post-doc

Dr. Pham Dinh Thanh
Past PhD students (researcher)

Dr. Nguyen Thi My Binh
Past PhD students (researcher)

Projects and Solutions

[VINIF2022] Transfer Learning for Combinatorial Optimization Problems
[USArmy2019] Multitasking Evolutionary Algorithms for Optimizing Artificial Neural Network and Graph-Based Models
[NAFOSTED2020] Towards energy unlimited IoT networks by nature-inspired algorithms

Latest Publications

Publications in 2026

  1. Anh Do Tuan, Ban Ha-Bang, Thi Thanh Binh Huynh, Tran Dao, Dinh Thanh Pham. MultiFatorial evolutionary algorithm with nodedepth encoding for inter-domain path computation under node-defined domain uniqueness constraint. Knowledge-Based Systems. 114910. 20/11/2025
  2. Bui Quoc-Trung. Dynamic programming for the exact pareto front in multi-objective discretization of imbalanced datasets. Information Sciences. 123292. 23/02/2026
  3. Bui Quoc-Trung, Pham Quang-Dung. Empirical Analysis of Strategies for Identifying and Incorporating Subtour Elimination Constraints in Branch-and-Cut Algorithms for Integer Programming. Lecture Notes in Networks and Systems. 629-641. 09/04/2025
  4. . .
  5. Nguyen Van Son, Pham Quang Dung, Bui Quoc Trung, Tran Thuy Chau. A proposed local search strategy and neighborhoods for solving a new variant of e-commerce districting problem. Computers and Industrial Engineering. 111843. 19/01/2026
  6. Bui Quoc-Trung, Van-Trong Nguyen, Thi-Thanh-Binh Huynh. Mixed Integer Program for Selection of Hardware Resource Configurations in a Spark Cluster. Smart Innovation, Systems and Technologies. 173-184. 23/05/2025
  7. Bui Quoc-Trung, Le Dai-Duong, Ta Hai-Tung. Integer Programming for Optimization of Blood Type Consistency in Family Records. Lecture Notes in Networks and Systems. 373-384. 30/11/2024

Publications in 2025

  1. Van Chien Trinh, Thu Ngo Tran Anh, Lam Nguyen Hoang, Ngo Hien Quoc, Chatzinotas Symeon, Binh Huynh Thi Thanh. Fairness Designs for Load Balancing Optimization in Satellite-Cell-Free Massive MIMO Systems. IEEE Transactions on Aerospace and Electronic Systems. 16343-16356. 30/10/2025
  2. Thanh Binh Huynh Thi, Van Duc Cuong, Van Son Nguyen, La Van Quan, Thi Hanh Nguyen. LSHADE-NGS: enhancing Q-coverage in directional sensor networks through navigated generation search. Neural Computing and Applications. 21659-21694. 03/07/2025
  3. Hai-Anh Tran; Cong-Son Duong; Trong-Duc Bui; Van Tong; Huynh Thi Thanh Binh. GAMR: Revolutionizing Multi-Objective Routing in SDN Networks With Dynamic Genetic Algorithms. IEEE Transactions on Emerging Topics in Computational Intelligence. 3147-3161. 15/02/2025
  4. Cui Wei, Ullah Ismat, Lin Weiming, Zhang Jupei, Chen Zhaowei, Yang Shuyi, Peng Wei, Zhuang Yin, Chen Wenjin, Cao Yi, Zhang Shujun, Jin Shengyang, Yang Liang. Multifunctional Sr2+/Zn2+ Co‐Doped Mesoporous Silica Nanoparticles in Injectable Hydrogel for Ameliorating Osteoporotic Osseointegration. Advanced Healthcare Materials. 15/06/2025
  5. Nguyễn Duy Vũ, Bùi Quốc Trung, Nguyễn Thúc Hương Giang. CHẤM ĐIỂM TÍN DỤNG CÁ NHÂN TỪ DỮ LIỆU THAY THẾ: TRƯỜNG HỢP CÁC TỔ CHỨC TÍN DỤNG TẠI VIỆT NAM. Tạp chí Quản lý và Kinh tế quốc tế. 14-28. 20/06/2025
  6. Thanh Pham Dinh, Anh Do Tuan. A Hybrid Multifactorial Evolutionary Algorithm for the Minimum s-Club Cover Problem. Communications in Computer and Information Science. 232-242. 12/12/2024
  7. Phan Duc Hung, Bui Trong Duc, Nguyen Thi Tam, Huynh Thi Thanh Binh. Pareto Front Grid Guided Multiobjective Optimization In Dynamic Pickup And Delivery Problem Considering Two-Sided Fairness. Genetic and Evolutionary Computation Conference (GECCO ’25). 277-285. Spain. 14/07/2025
  8. Dao Phan-Khai, Vu Van-Tan, Bui Quoc-Trung. A Tool for Preventing Consanguineous Marriages Using Vietnam’s National Residents Database. Communications in Computer and Information Science. 43-54. 11/12/2024
  9. Vu Quang Truong, Trinh The Minh, Nguyen Thi Hanh, Trinh Van Chien, Huynh Thi Thanh Binh, Nguyen Xuan Thang, Huynh Cong Phap. SPARTA-GEMSTONE: A two-phase approach for efficient node placement in 3D WSNs under Q-Coverage and Q-Connectivity constraints. Journal of Network and Computer Applications. 104175. 17/03/2025
  10. Tam Nguyen Thi, Anh Ngo Duy, Tung Dao Van, Huynh Thi Thanh Binh, Vinh Le Trong. Evolving routing and sequencing policies for dynamic vehicle routing problem with time windows. Applied Soft Computing. 114234. 05/11/2025
  11. Bui Quoc Trung. Exact and Heuristic Approaches for Anti-aircraft Mission Planning for Defensive Missile Battalions. Military Operations Research (United States). 61-81. 12/01/2026
  12. Ban Hà Bằng, Phạm Đăng Hải. A multi-population multi-tasking Tabu Search with Variable Neighborhood Search algorithm to solve post-disaster clustered repairman problem with priorities. Applied Soft Computing. 16/12/2024
  13. Nguyen Tuan-Anh, Pham Quang-Dung, Bui Quoc-Trung. Framework for Detecting and Suggesting Corrections for Missing and Inconsistent Data in Vietnam’s National Residents Database. Lecture Notes in Networks and Systems. 151-163. 04/06/2025
  14. Giang Tran Thi Cam, Binh Huynh Thi Thanh, Luong Ho Viet Duc, Hoang Nguyen Huy, Huy Do Quoc. Fast marching firework method for multi-goal mobile robot path planning in complex obstacle maps. Intelligent Service Robotics. 1467-1484. 28/09/2025
  15. Tran Hai Anh, Binh Huynh Thi Thanh, Mellouk Abdelhamid. Federated Learning for Network Traffic Classification: A Knowledge Consolidation Approach. IEEE Transactions on Network Science and Engineering. 797-814. 05/07/2025
  16. Thang Nguyen Xuan, Hanh Nguyen Thi, Son Nguyen Van, Tan Nguyen Phuc, Hung To Quang, Chien Trinh Van, Binh Huynh Thi Thanh. Propagation-aware Q-coverage and Q-connectivity network design in relay-aided IoT sensor systems using heuristic and genetic algorithms. Neural Computing and Applications. 12031-12058. 18/02/2025
  17. Dat Pham Vu Tuan, Doan Long, Binh Huynh Thi Thanh. HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMs. Proceedings of the AAAI Conference on Artificial Intelligence. 26931-26938. 26/02/2025
  18. Pham Dinh Thanh, Do Tuan Anh, Nguyen Hung Son, Nguyen Duc Thai. New Local Search Strategy for the Minimum s-Club Cover Problem. Informatica (Slovenia). 495-506. 03/09/2025
  19. My Binh Nguyen Thi, Minh Tam Le Vu, Duc Luong Ho Viet, Chien Trinh Van, Thanh Binh Huynh Thi. Reinforcement Learning-based Genetic Algorithm for Computation Offloading Optimization in UAV-assisted MEC Systems. The Genetic and Evolutionary Computation Conference Companion. 307-310. Malaga, Spain. 14/07/2025
  20. Duc Luong Ho Viet, Chien Trinh Van, Nguyet Anh Lang Hong, Binh Huynh Thi Thanh. Hybrid Deterministic and Metaheuristic Optimization for Physical Adversarial Attack on End-to-End Autoencoder Wireless Communication Systems. The Genetic and Evolutionary Computation Conference Companion. 259-262. Malaga, Spain. 14/07/2025
  21. Tran Thanh Hai, Nguyen Dac Tam, Ngo Minh Duc, Doan Long, Luong Ngoc Hoang, Binh Huynh Thi Thanh. Kernelshap-nas: a shapley additive explanatory approach for characterizing operation influences. Neural Computing and Applications. 11755-11771. 04/02/2025
  22. Ho Viet Duc Luong, Huynh Thi Thanh Binh, Nguyen Thi My Binh, Trinh Van Chien. Mobile device-target association optimization for connectivity enhancement in wireless IoT sensor networks. Cluster Computing. 978. 02/07/2025
  23. . .
  24. Tran Hue Thi, Hoang Ky Tuan, Nguyen Phuong Khanh, Binh Huynh Thi Thanh. A bi-objective Medical Sampling Service System. Genetic and Evolutionary Computation Conference (GECCO ’25 Companion). 435-438. 14/07/2025
  25. Duc Bui Trong, Chien Trinh Van, Ngo Hien Quoc, Binh Huynh Thi Thanh. Multi-Objective Signal Optimization to Balance Multiple Conflicting Metrics in RIS-Assisted MIMO Systems. Genetic and Evolutionary Computation Conference (GECCO ’25 Companion). 915-918. Malaga, Spain. 14/07/2025
  26. Van Tong; Cuong Dao; Hai Anh Tran; Duc Tran; Huynh Thi Thanh Binh; Nam-Thang Hoang. Encrypted Traffic Classification Through Deep Domain Adaptation Network With Smooth Characteristic Function. IEEE Transactions on Network and Service Management. 331-343. 24/01/2025
  27. Hung Phan Duc, Tam Nguyen Thi, Thanh Binh Huynh Thi. Adaptive ant colony optimization for solving dynamic vehicle and drone routing with time window constraints. Evolutionary Intelligence. 24/08/2025
  28. Son Nguyen Van, Hanh Nguyen Thi, Minh Trinh The, Binh Huynh Thi Thanh, Thang Nguyen Xuan. Heuristic and approximate Steiner tree algorithms for ensuring network connectivity in mobile wireless sensor networks. Journal of Network and Computer Applications. 104155. 24/02/2025
  29. Nguyen Thi Ha Nhan, Bui Quoc Trung. Fairness in Credit Scoring: A Bibliometric Analysis of the Last 15 Years. ICGFSD INTERNATIONAL CONFERENCE ON GREEN FINANCE FOR SUSTAINABLE DEVELOPMENT. FBU. 25/06/2025

Publications in 2024

  1. Hung Tran Huy, Nguyen Thi Tam, Huynh Thi Thanh Binh, Le Trong Vinh. Two-stage metaheuristic for reliable and balanced network function virtualization-enabled networks. Soft Computing. 30/12/2023
  2. Trinh Van Chien, Bui Trong Duc, Ho Viet Duc Luong, Huynh Thi Thanh Binh, Hien Quoc Ngo, Symeon Chatzinotas. Solving Indefinite Communication Reliability Optimization for RIS-Aided Mobile Systems by an Improved Differential Evolution. GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion. 651-654. Melbourne, Australia. 14/07/2024
  3. Bui Quoc Trung, Vuong Hoang Minh, Nguyen Thi Hoai Linh, Bui Thi Mai Anh. A Novel Dynamic Programming Method for Non-Parametric Data Discretization. Intelligent Information and Database Systems - ACIIDS 2024. 111-120. UAE. 15/04/2024
  4. Do Tuan Anh, Huynh Thi Thanh Binh, Ban Ha Bang, Nguyen Duc Thai, Phung Bao Ha. A multi-population multi-tasking variable neighborhood search algorithm with diversity enhancements for inter-domain path computation problem. Swarm and Evolutionary Computation. 1-15. 01/02/2024
  5. Nguyễn Bình Long, Đỗ Tuấn Anh, Huỳnh Thị Thanh Bình, Ban Hà Bằng. An online transfer learning based multifactorial evolutionary algorithm for solving the clustered Steiner tree problem. Knowledge-Based Systems. 26/04/2024
  6. Van Son Nguyen, Quang Dung Pham, Thanh Trung Huynh. Modelling and solving a real‑world truck‑trailer scheduling problem in container transportation with separate moving objects. OPSearch. pages 628–661. 28/11/2023
  7. Nguyen Thi Tam, Le Huy Duong , Huynh Thi Thanh Binh, Le Trong Vinh. Subswarm-guided ant colony optimization with enhanced pheromone update mechanism and beam search for VNF placement and routing. Applied Soft Computing. 06/01/2024
  8. Tung Nguyen, Tung Pham, Linh Ngo Van , Ha-Bang Ban , Khoat Than. Out-of-vocabulary handling and topic quality control strategies in streaming topic models. Neurocomputing. 128757. 19/10/2024
  9. Thanh Pham Dinh, Long Nguyen Binh, Vinh Le Sy, Binh Huynh Thi Thanh. Evolutionary multitasking algorithm based on a dynamic solution encoding strategy for the minimum s-club cover problem. Evolutionary Intelligence. 1-24. 04/11/2024
  10. Trinh Van Chien; Bui Trong Duc; Ho Viet Duc Luong; Huynh Thi Thanh Binh; Hien Quoc Ngo; Symeon Chatzinotas. Solving Indefinite Communication Reliability Optimization for RIS-Aided Mobile Systems by an Improved DE. The Genetic and Evolutionary Computation Conference (GECCO). 1-4. Melbourne , Australia. 14/07/2024
  11. Binh Minh Nguyen; Thieu Nguyen; Quoc-Hien Vu; Tran Huy Hung; Tran Hoang Hai; Huynh Thi Thanh Binh; Van-Dang Tran. Dholes Hunting-A Multi-Local Search Algorithm Using Gradient Approximation and Its Application for Blockchain Consensus Problem. IEEE Access. 93333-93349. 11/06/2024
  12. Trinh Van Chien, Bui Trong Duc, Ho Viet Duc Luong, Huynh Thi Thanh Binh, Hien Quoc Ngo, Symeon Chatzinotas. Active and Passive Beamforming Designs for Communication Reliability in RIS-Assisted MIMO Systems. IEEE Transactions on Wireless Communications. 18838-18854. 02/10/2024
  13. Trinh Van Chien; Ngo Tran Anh Thu; Nguyen Hoang Lam; Huynh Thi Thanh Binh; Nguyen Thi My Binh. On the Performance of User Association in Space-Ground Communications with Integer-Coded Genetic Algorithms. The Genetic and Evolutionary Computation Conference (GECCO). 1-8. Melbourne, Australia. 14/07/2024
  14. T. K. Lai, and I. L. Ngo. An investigation on the thermo-electrohydraulic performance of novel ECF micro-pump.. International Journal of Heat and Mass Transfer. 29/09/2024
  15. Trinh Van Chien, Bui Trong Duc, Ho Viet Duc Luong, Huynh Thi Thanh Binh, Hien Quoc Ngo, Symeon Chatzinotas. Active and Passive Beamforming Designs for SER Minimization in RIS-Assisted MIMO Systems. IEEE Transactions on Wireless Communications. 18838-18854. 02/10/2024
  16. Sikandar Ali Qalati, MengMeng Jiang, Samuel Gyedu, and Emmanuel Kwaku Manu. Do Strong Innovation Capability and Environmental Turbulence Influence the Nexus Between Customer Relationship Management and Business Performance?. Business Strategy and the Environment. 02/07/2024
  17. Ha Minh Hieu, Phan Duc Hung, Tran Duc Chinh, Van Duc Cuong, Dao Van Tung, Huynh Thi Thanh Binh. Alimentation Deep Multiple Optimal Ant Colony Optimization to solve Vehicle Routing Problem with Time Windows. The Genetic and Evolutionary Computation Conference. 14/07/2024
  18. JYE Tin, WW Tan, AA Bakar, MS Mahali, FF Lothai, NF Mohammad, SSA Hassan & KF Chin. A Conceptual Design of Sustainable Solar Photovoltaic (PV) Powered Corridor Lighting System with IoT Application. ICREEM 2022. 09/03/2024
  19. Do Tuan Anh a, Huynh Thi Thanh Binh a, Do Luong Kien a, Nguyen Hoang Long a, Tran Cong Dao a b, Ha-Bang Ban a. Node-depth based Genetic Algorithm to solve Inter-Domain path computation problem. Knowledge-Based Systems. 04/11/2023
  20. . .
  21. Ha-Bang Ban, Huynh Thi Thanh Binh, Tuan Anh Do, Cong Dao Tran, Su Nguyen. A hybrid and adaptive evolutionary approach for multitask optimization of post-disaster traveling salesman and repairman problems. Computers & Operations Research. 1-20. 12/03/2024
  22. Trinh Thi Ha, Nguyen Trung Dung, Nguyen Thanh Huong, Tran Trong An, Pham Van Tuan, Vu Ngoc Hung, Chu Manh Hoang. Investigating the coupling length of two triangle hybrid gap plasmonic waveguides. The International Conference on Advanced Materials and Technology (ICAMT 2024). 10-13. Hanoi. 09/10/2024
  23. Le Tien Thanh, Ta Bao Thang, Le Van Cuong, Huynh Thi Thanh Binh. Multitask Augmented Random Search in deep reinforcement learning. Applied Soft Computing Journal. 04/04/2024
  24. Quang Truong Vu, Phuc Tan Nguyen, Thi Hanh Nguyen, Thi Thanh Binh Huynh, Trinh Van Chien, Mikael Gidlund. Striking the Perfect Balance: Multi-Objective Optimization for Minimizing Deployment Cost and Maximizing Coverage with Harmony Search. Journal of Network and Computer Applications. 104006. 23/08/2024
  25. Sikandar Ali Qalati, Domitilla Magni, and Faiza Siddiqui. Senior Management's Sustainability Commitment and Environmental Performance: Revealing the Role of Green Human Resource Management Practices.. Business Strategy and the Environment. 02/08/2024
  26. T. K. Lai, and I. L. Ngo. A new design and optimization of VD-ECF micro-pump: Advancements in electrohydraulic performance. Physics of Fluids. 29/07/2024
  27. Nguyen Thi Tam, Tran Ho Khanh Ly, Bui Trong Duc, Tran Huy Hung, Huynh Thi Thanh Binh. Multi-Objective Virtual Network Functions Placement and Traffic Routing Problem. 2024 IEEE Congress on Evolutionary Computation (CEC). 01-08. 30/06/2024
  28. Nguyen Thi My Binh, Huynh Thi Thanh Binh, Ho Viet Duc Luong, Nguyen Tien Long, Trinh Van Chien. An efficient exact method with polynomial time-complexity to achieve k-strong barrier coverage in heterogeneous wireless multimedia sensor networks. Journal of Network and Computer Applications. 19/08/2024
  29. Thanh Tran Hai, Doan Long, Luong Ngoc Hoang, Huynh Thi Thanh Binh. THNAS-GA: A Genetic Algorithm for Training-free Hardware-aware Neural Architecture Search. GECCO. 1128-1136. 14/07/2024
  30. T. K. Lai, and I. L. Ngo. An investigation on the electrohydraulic performance of novel ECF micro-pump with NACAshaped electrodes. Theoretical and Computational Fluid Dynamics. 29/02/2024
  31. Tran Thi Cam Giang, Dao Tung Lam , Huynh Thi Thanh Binh, Dinh Thi Ha Ly, Do Quoc Huy. BWave framework for coverage path planning in complex environment with energy constraint. Expert Systems with Applications. 123277. 16/01/2024
  32. Ban Hà Bằng, Phạm Đăng Hải. Metaheuristic for solving the Deliveryman Problem with Drone. Computing and Informatics. 1184–1212. 08/12/2023
  33. Thi-Mai-Anh Bui, Van-Tri Do, Minh Vu Le, Quoc-Trung Bui. Dynamic Difficulty Coefficient in Search-Based Software Testing: Targeting to Hard Branch Coverage. Genetic and Evolutionary Computation Conference - GECCO 2024. 791-794. Melbourne. 14/07/2024
  34. Trần Thị Huế; Bảo Nguyễn; Quốc Nguyễn; Phạm Phú Mạnh; Nguyễn Khánh Phương; Huỳnh Thị Thanh Bình; Đặng Quang Thắng. The Vehicle Routing Problem with Drones and Flexibility Demands. IEEE Congress on Evolutionary Computation. 1-8. Yokohama, Japan. 30/06/2024