Recently, Professor Fu Chenyi from the School of Management, as the first author, has published online the research paper entitled "Rank‑Constrained Mixed‑Integer Optimization for Heterogeneous Sensor Location in Route Reconstruction" in INFORMS Journal on Computing. His co‑authors include Assistant Professor Li Chen from the University of Sydney and Dr. Zhiyuan Lou from the Technical University of Munich. INFORMS Journal on Computing is a top journal in operations research and one of the 24 leading academic journals for business schools (UTD‑24) selected by the University of Texas at Dallas.

(Link: https://pubsonline.informs.org/doi/10.1287/ijoc.2024.0965)

This paper proposes a mixed‑integer rank‑constrained optimization model for the heterogeneous traffic‑sensor location problem oriented toward route reconstruction. Generally, rank constraints are non‑convex and cannot be represented by mixed‑integer convex optimization models. Nevertheless, drawing on the model properties and the inherent structure of rank constraints identified in this work, it is proven that the proposed model is equivalent to a mixed‑integer linear optimization formulation. To boost computational efficiency, a logic‑based Benders decomposition algorithm is developed, featuring an enhanced master problem and custom‑built feasibility cuts. For large‑scale problem instances, a scalable two‑step heuristic is further presented: an upper bound for the mixed‑integer optimization model is first constructed, and a greedy strategy is then applied to eliminate redundant sensors. Numerical experiments demonstrate that the logic‑based Benders decomposition algorithm achieves up to two orders‑of‑magnitude speed‑up compared with state‑of‑the‑art commercial solvers. Moreover, the two‑step heuristic exhibits excellent scalability while retaining acceptable solution quality relative to exact methods. On large‑scale instances, it consistently outperforms benchmark alternatives in both computation time and solution quality.

About the speaker:Fu Chenyi is Professor and Doctoral Supervisor in the Department of Management Science and Engineering, School of Management. His research interests include robust optimization and urban traffic operation optimization. He has 15 published journal papers as first or corresponding author, including one paper apiece in four top management‑science journals: Operations Research (UTD‑24), Production and Operations Management (UTD‑24), Manufacturing & Service Operations Management (UTD‑24), and INFORMS Journal on Computing (UTD‑24). He has published six papers in Transportation Research Part B, a top journal in transportation operations research, and three papers in European Journal of Operational Research, a high‑level journal for operations optimization. He has received the Best Paper Award and Outstanding Doctoral Dissertation Award from the International Symposium on Computational Transportation Science. He is a recipient of the Shaanxi Sanqin Talents Introduction Program (Youth Project) and the 2025 Doctoral Innovation Incentive Program of the Chinese Systems Engineering Society. He currently presides over the NSFC Youth Project (Category‑C) and one Fundamental Research Funds for the Central Universities (Social Sciences) Project.

(Written by:Scientific Research Office Reviewed by:Jia Ming)