Professor Enkhbat Rentsen

Professor Enkhbat Rentsen is a Mongolian mathematician, Professor Emeritus at the National University of Mongolia, and an Academician of the Mongolian Academy of Sciences. His research focuses on global optimization, quasiconvex programming, optimal control and game theory, with contributions to both mathematical theory and its practical applications.

He earned his Ph.D. in Applied Mathematics from Irkutsk State University, Russia, in 1990. He also holds a master’s degree in economics from the National University of Mongolia and a Doctor of Science degree from the Mongolian Academy of Sciences. His international experience includes visiting appointments at Kyoto University, Humboldt University of Berlin and Curtin University, alongside research fellowships supported by Fulbright, JSPS and DAAD.

His research includes work on sphere-packing problems, Malfatti’s problem, and Anti-Nash and Anti-Berge equilibrium concepts in game theory. In mineral processing, he has co-authored studies applying mathematical optimization to copper recovery and operating conditions in copper–molybdenum flotation at Erdenet Mining Corporation. He is also a co-editor of Springer’s Optimization, Simulation and Control (2023).

A recipient of Mongolia’s State Prize in 2012, Professor Enkhbat has made sustained contributions to mathematical research and doctoral education. The National University of Mongolia recognized these contributions by awarding him the title of Professor Emeritus in 2024.

This topic was motivated by an ore-blending optimization problem formulated at the Erdenet Mining Corporation of Mongolia. This study develops a cost-minimization model for short-term ore extraction planning under copper grade constraints using operational data from a large open-pit mine. A sphere packing  framework is formulated to determine the optimal extraction quantities from 25 mining faces while satisfying planned production targets and minimum average copper grade requirements. The model incorporates face-specific extraction capacities and operating costs. Numerical optimization results demonstrate that selectively prioritizing high-grade, low-cost faces significantly reduces total operating costs while maintaining planned ore quality. The sphere packing approach allows us to find optimal ranges of decision variables which represent the extraction quantity from unit within the planning horizon. The proposed sphere packing approach provides a practical and computationally efficient decision-support tool for short-term mine production planning.