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Open-Pit Mine Scheduling Optimizer

Large-scale optimization models and solution methods for long-term mine planning.

Key Features

• mixed-integer programming formulation
• precedence constraints
• resource constraints
• cutting planes
• rolling-horizon methods
• Large Neighborhood Search (LNS)

Tech Stack C++, Gurobi, OpenMP

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Relax-and-Repair Optimization Framework

A framework for generating feasible solutions for difficult large-scale MILP models.

Core Concepts

• constraint relaxation
• slack variables
• penalty-based repair
• feasibility-driven optimization

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Large Neighborhood Search Methods

Implementation of LNS for large combinatorial optimization problems.

Includes

• destroy and repair operators
• adaptive search strategies
• large-scale neighborhood exploration
• improvement-based optimization workflows

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Optimization Software Development

Development of modular optimization codebases for:

• large-scale MILP models
• heuristic integration
• warm starts and restart workflows
• computational experimentation
• industrial optimization studies

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Machine Learning for Optimization

Exploration of machine learning techniques to enhance optimization performance.

Directions

• learned heuristics
• solver guidance
• intelligent initialization
• data-driven decision support

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Future Application Directions

• Transportation optimization
• Airline and flight operations
• Sustainable energy systems
• Data-driven industrial optimization