Research

My doctoral research focuses on the Open-Pit Mine Production Scheduling Problem (OPMPSP), a large-scale mixed-integer optimization problem arising in mining operations.

These problems involve:

very large decision spaces
complex precedence relationships
multi-period planning decisions
operational and economic trade-offs
substantial computational difficulty at industrial scale

Research Contributions

My work focuses on improving solvability through:

Cutting planes for strengthening MILP formulations
Extended formulations for improving model structure
Relax-and-repair frameworks for rapidly obtaining feasible solutions
Rolling-horizon decomposition
Large Neighborhood Search (LNS) for solution improvement
Research software development for large computational studies

Research Themes

Mixed-integer programming
Large-scale optimization
Combinatorial optimization
Heuristics and metaheuristics
Algorithm design
Research software engineering

Application Areas

Mining operations
Mine production scheduling
Transportation and logistics
Aviation and flight operations
Industrial decision support systems

Research Vision

My goal is to develop optimization methods that are:

mathematically strong
computationally scalable
practically deployable

for large industrial systems where exact methods, heuristics, and software design must work together.