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          Department of Systems Engineering and Engineering Management

                                  The Chinese University of Hong Kong

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Date: Friday, April 17, 2026, 10:30 am to 11:30 am HKT

Venue: ERB513, The Chinese University of Hong Kong

Title: A new data-driven framework for balancing user accessibility and facility load fairness

Speaker: Prof. Bismark Singh, University of Southampton

Abstract

Typically, within combinatorial facility location problems, fairness is defined in terms of accessibility of users. However for the class of undesirable facility location problems, fairness between the usage of facilities becomes especially important. Limited research exists on this notion of fairness. In a series of works, we have attempted to close this gap by developing new classes of discrete optimization models for the allocation of populations of users to facilities such that access for users is balanced with a fair utilization of facilities. The optimality conditions of the underlying nonconvex quadratic models state the precise balance between accessibility and fairness. Further, we define new axioms of fairness and a metric to quantify the extent to which fairness is achieved in both optimal and suboptimal allocations. We show that a continuous relaxation of our central model is sufficient to achieve a perfect extent of fairness, while a special case reduces to the classical notion of proportional fairness. We present computational results using actual data from the state of Bavaria in Germany. The main part of this work is based on two articles published with my students both in the INFORMS Journal on Computing. In ongoing work, we are studying supermodularity properties of this new class of objective functions. All presented materials are published and/or in the public domain.

Biography

Bismark Singh is an associate professor in operational research in the School of Mathematical Sciences at the University of Southampton, UK. He received a habilitation (2023) in mathematics from the Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany; PhD and MSc degrees in operations research from The University of Texas (UT) at Austin, US; and, a B.Tech. (2011) degree in chemical engineering from the Indian Institute of Technology (IIT) Delhi. Between 2016 and 2019 he held positions at Sandia National Laboratories, US in the Discrete Math & Optimization group. His research has been funded by agencies including the Deutsche Forschungsgemeinschaft (DFG), the Horizon 2020 program, the Bavarian State Ministry for Science and Art, and the US Department of Energy. He is a Senior Member of IEEE, a Fellow of Institute of Mathematics and its Applications, and an Associate Fellow of The OR Society. He is the Winner of the 2023 Mathematics Young Investigator Award. In 2024-25, he was a Distinguished Research Fellow at TU Dresden, Germany. For further information, visit: https://bissi1.github.io/.