We design and implement advanced decision optimisation solutions by
integrating mathematical optimisation, machine learning, and
data-driven modelling to support high-impact industrial decisions.
What We Do
OptMining supports organisations facing complex planning, scheduling,
and operational challenges where uncertainty, scale, and constraints
make traditional approaches ineffective.
Key Focus Areas
Decision Optimisation & Planning
Advanced optimisation models for strategic planning, scheduling,
and resource allocation in large-scale industrial systems.
Machine Learning–Driven Decision Support
Data-driven models that integrate prediction, optimisation,
and learning to support decisions under uncertainty.
Industrial Systems & Digital Twins
Decision-support frameworks combining simulation, optimisation,
and system-level analytics across energy, mining, and infrastructure.
Industries We Work With
We apply machine learning and optimisation to complex, high-impact industrial domains where decisions involve uncertainty, scale, and operational constraints.
Energy & Infrastructure
Optimisation and decision-support for power systems, renewable integration, energy markets, storage planning, and large-scale infrastructure investment under uncertainty.
Mining & Resources
Strategic mine planning, production scheduling, resource allocation, and risk-aware optimisation across open-pit and complex resource extraction systems.
Manufacturing & Supply Chains
Data-driven optimisation of production systems, logistics networks, inventory policies, and end-to-end supply-chain decisions.
How We Work
Our approach combines rigorous mathematical optimisation with modern machine learning to support high-stakes decisions in complex industrial systems. We focus on transparency, scalability, and real-world feasibility rather than black-box automation.
Problem Structuring
We work with stakeholders to formalise objectives, constraints, uncertainties, and decision boundaries, translating real-world challenges into mathematically sound decision problems.
Data & Modelling
Relevant operational, economic, and environmental data are integrated with domain knowledge to build predictive and optimisation-ready models that reflect system behaviour.
Optimisation, Learning, Decision Support & Deployment
Advanced optimisation and machine learning methods explore trade-offs, generate feasible solutions, and support decision-making under uncertainty, delivered through interpretable decision-support tools and actionable recommendations integrated into existing workflows.
Selected Capabilities
Our capabilities span optimisation, machine learning, and decision analytics, enabling tailored solutions across diverse industrial contexts.
Mathematical Optimisation
Linear, mixed-integer, nonlinear, and multi-objective optimisation for planning, scheduling, and resource allocation problems.
Machine Learning for Decision Support
Predictive and prescriptive models that enhance optimisation through forecasting, pattern discovery, and uncertainty-aware learning.
Large-Scale & Constrained Systems
Methods designed to handle high-dimensional decision spaces, complex constraints, and computational scalability challenges.
Opt-Mining 