We are a research group of Operations Research at Beijing Foreign Studies University. Our research interests include topics in combinatorial optimization, global optimization and machine learning.



Ph.D., Associate Professor

Xiaosong DING
Ph.D., Professor


Chong FENG

Kaiwen LI




Peiling YU, MSE in Systems Engineering, University of Pennsylvania.
Sidian LIN, Ph.D. student with full scholarship at Harvard University.
Yili ZHU, M.Sc. in Operations Research, Columbia University.


Combinatorial Optimization

This topic is a variant of Vehicle Routing Problem Heuristics (VRPH), which focuses on Multi-period Dynamic Technician Routing and Scheduling Problems. Basically, we intend to take advantage of Approximate Dynamic Programming (ADP) in order to overcome the curse of dimensionality in dynamic programming. It seems relatively demanding in computer science and combinatorial optimization. To be specific, we implement various deterministic or heuristic algorithms, measure their performance, and try to develop new approaches, with C++.

Global Optimization

Our research primarily concerns various computational issues in cutting plane methods for solving Disjoint Bilinear Programming and Integer Progamming (DBLP). For example, the neighbourhood enumeration problem, degeneracy removal, etc. Recently, we are also aware of some heuristic approaches. Needless to say, the point still lies in how to balance the precision and computational time during the development of a practical algorithm.

Machine Learning

Our research in this field focuses on the combination of machine learning theory and applications in operations management. Based on state-of-the-art techniques, we are developing efficient algorithms for specific problems such as improving the process of denitration. In general, we intend to discover inherent manifold structure of high-dimentional data and hence figure out advanced methods for dealing with missing data. What's more, we are working on explainable machine learning through the pattern of real-world data and how would models react accordingly.


[2022.06] Peiling graduated from BFSU and will pursue her master's degree at University of Pennsylvania, congratulations to her!
[2022.06] Hu successfully passed the entrance exam and will start his Ph.D. life in September, congratulations to him!
[2022.04] Kaiwen will start his postgraduate life due to his outstanding performance in the National Graduate Entrance Examination, congratulations to him!
[2021.07] Sidian graduated from BFSU and is currently pursuing her Ph.D. degree at Harvard Univeristy, congratulations to her!
[2021.04] Kaiwen and his team are designated as Finalist Winner in 2021 ICM (The Interdisciplinary Contest in Modeling), congratulations to them!

We will defend in a manly way true science, extend and embellish it, not for gain's sake or for attaining a vain shine of glory, but in order that the light of truth shine bright and expand.


  • 基于直觉模糊混合熵的投资组合风险度量模型
    张宇卓, 丁晓松
  • Optimal Production-inventory Policy for a Periodic-review Energy Buy-back System over an Infinite Planning Horizon
    Hongqiao CHEN, Xiaosong DING, Jihong ZHANG, and Huayi LI
    Asia-Pacific Journal of Operational Research, 37(02), April, 2020 (SCI)
  • Location of a Conservative Hyperplane for Cutting Plane Methods in Disjoint Bilinear Programming
    Xi CHEN, Jihong ZHANG, and Xiaosong DING
    Optimization Letters, 13(7):1677-1692, 2019 (SCI)
  • An Approximate Dynamic Programming Method for the Multi-period Technician Scheduling Problem with Experience-based Service Times and Stochastic Customers
    Xi CHEN, Michael HEWITT and Barrett W. THOMAS
    International Journal of Production Economics, 196:122-134, 2018 (SCI)
  • Multi-Period Technician Scheduling with Experience-based Service Times and Stochastic Customers
    Xi CHEN, Barrett W. THOMAS, and Michael HEWITT
    Computers and Operations Research, 82:1-14, 2017 (SCI)
  • Degeneracy Removal in Cutting Plane Methods for Disjoint Bilinear Programming
    Jihong ZHANG, Xi CHEN, and Xiaosong DING
    Optimization Letters, 11(3):483-495, 2017 (SCI)
  • The Technician Routing Problem with Experience-based Service Times
    Xi CHEN, Barrett W. THOMAS, and Michael HEWITT
    Omega, 61:49-61, 2016 (SCI)
  • Pricing and Inventory Control Strategy for a Periodic-Review Energy Buy-Back System
    Jihong ZHANG, Hongqiao CHEN, Xiaosong DING, and Xian LI
    Journal of Systems Science and Complexity, 29(4):1018-1033, 2016 (SCI)
  • 基于云模型和熵权的离岸服务外包承接地能力综合评价
    《数学的实践与认识》,45(10):131-137, 2015 (CSCD)
  • 能源回购补偿机制下基于无限阶段折扣准则的最优生产与库存策略
    《运筹与管理》,5:109-119, 2014 (CSSCI)
  • 工资粘性、货币冲击与价格贸易条件
    《经济研究》,8:81-93, 2013 (CSSCI)
  • A Joint Pricing and Inventory Control Problem under an Energy Buy-back Program
    Xiaosong DING, Jihong ZHANG, and Xi CHEN
    Operations Research Letters, 40(6):516-520, 2012 (SCI)
  • 能源回购补偿机制下的联合生产与定价策略
    《系统科学与数学》,31(10):1297-1305, 2011 (CSCD)
  • Disjoint Programming in Computational Decision Analysis
    Xiaosong DING, Mats DANIELSON, and Love EKENBERG
    Journal of Uncertain Systems, 4(1):4-13, 2010
  • Accelerating Convergence of Cutting Plane Algorithms for Disjoint Bilinear Programming
    Xiaosong DING, and Faiz AL-KHAYYAL
    Journal of Global Optimization, 38(3):421-436, 2007 (SCI)

Conference Papers

  • A Real Time Scheduling Scheme For Food Delivery
    Xiaosong DING, Hu LIU, and Xi CHEN
    IEEE International Conference on Emergency Science and Information Technology (ICESIT), 22-24 November, 2021 (EI)
  • On Supply Chain Performance and Efficiency under Purchase Order Financing together with Reverse Factoring Financing
    Jihong ZHANG, Jinyan GAO, Xi CHEN, Xiaosong DING, Ruohong CHEN, and Linlin YANG
    16th International Conference on Service Systems and Service Management (ICSSSM'19), Shenzhen, China, 2019 (EI)
  • Method Development and Comparative Study of P2P Agricultural Loan Selection
    Di WANG, Yili ZHU, and Xi CHEN
    15th International Conference on Service Systems and Service Management (ICSSSM'18), Hangzhou, China, 2018 (EI)
  • The Pricing Strategy for the Dual Channel Supply Chain with Pre-Sale Service
    Zehua YANG, Jihong ZHANG, and Xi CHEN
    15th International Conference on Service Systems and Service Management (ICSSSM'18), Hangzhou, China, 2018 (EI)
  • Location of a Conservative Hyperplane for Disjoint Bilinear Programming Based on Distances
    Jihong ZHANG, Jinyan GAO, Tian YANG, Xi CHEN, and Xiaosong DING
    15th International Conference on Service Systems and Service Management (ICSSSM'18), Hangzhou, China, 2018 (EI)
  • Manufacturer's Optimal Preselling Discount Rate with Sufficient Initial Working Capital
    Xiaosong DING, Jihong ZHANG, and Yanjun LI
    13th International Conference on Service Systems and Service Management (ICSSSM'16), Kunming, China, 2016 (EI)
  • Optimal Contract and Pricing Decisions for Online Display Advertisement
    Jihong ZHANG, Xiaoxi LIN, and Xiaosong DING
    12th International Conference on Service Systems and Service Management (ICSSSM'15), Guangzhou, China, 2015 (EI)

Under Review

[2022.07] Technician Routing and Scheduling with Reinforcement Learning-based Implicit Cross-training Strategy
Xi CHEN, Kaiwen LI, Sidian LIN, and Xiaosong DING, European Journal of Operational Research
[2022.07] Death Code: An Analysis of the Influencing Factors of the Immediate Execution of the Death Penalty in Homicide Cases
Yanlong ZHANG, Mengqi BI, Xiaosong DING, and Xi CHEN
[2022.07] Domino Pyramid: Evidence from the International Agricultural Trade Network
Xi CHEN, Kaiwen LI, and Xiaosong DING, Food Security
[2022.03] Gradient Boosting Decision Tree in the Prediction of NOx Emission
Xiaosong DING, Chong FENG, Peiling YU, Kaiwen LI, and Xi CHEN, Energy

Working Papers

[2022.07] Developing Polar Cuts at a Degenerate Vertex in Disjoint Bilinear Programming
Xi CHEN, Kaiwen LI, Sidian LIN, and Xiaosong DING


In mathematical terms, an optimization problem is the problem of finding the best solution among the set of all feasible solutions. VRPH, a subject with numerous real-life applications, is actually a combinatorial optimization problem much more complicated than the well-known NP-hard Traveling Salesman Problem. As a result, exact optimal solutions can only be derived for small size problems, whereas for large-scale or real-life instances, metaheuristics must come into play. It is a prolific area in intelligent logistics, a sub-branch of artificial intellgence. For the development of practical optimization methods, we focus on various computational issues arising in linear programming and integer programming, e.g., deterministic global optimization methods that take advantage of cutting planes.

We are in favor of students with strong research interests and self-learning ability:
  • Freshmen or sophomores;
  • Seniors with promised graduate study; and
  • First-year graduates in pursuit of Ph.D. degrees.

The knowledge to be covered includes but not limited to:
  • Optimization: Linear programming, combinatorial optimization, ADP;
  • Computer Science: Linux, C/C++, Python, data structure, algorithm design and analysis, machine learning.
Besides, skills in MATLAB and LaTeX may greatly facilitate the entire process of your graduate study.