Multi-objective optimisation models for forecasting and decision-making in supply chains and energy systems

Overview

This PhD project will focus on developing and evaluating multi-objective optimisation models that simultaneously optimise forecasting accuracy and operational decisions in complex systems.

Research activities

Key activities include:

• comprehensive literature review, upgrading knowledge
• survey existing methods in forecast-based optimisation, decision-centric forecasting, and multi-objective optimisation
• formulate novel optimisation models integrating forecast generation (e.g. probabilistic, hierarchical, or physics-informed forecasts) with downstream decisions (e.g. inventory control, load balancing)
• implement and benchmark evolutionary algorithms, Pareto optimisation, or gradient-based methods for solving these models
• apply the models in one or two domains:
  • supply chains (e.g. inventory planning, demand forecasting)
  • energy systems (e.g. load forecasting, renewable energy scheduling)
• explore trade-offs between objectives such as forecast accuracy (e.g. MASE, CRPS) and decision quality (e.g. cost, service level, energy efficiency).

Outcomes

• Development of new multi-objective optimisation models for forecast-decision integration.
• At least two high-quality journal publications in forecasting, operations research, or energy systems.
• Open-source code and reproducible benchmarks for academic and industry use.
• Practical impact in industry applications, through partnerships with supply chain or energy companies.

Skills and experience

• A strong background in optimisation, mathematical modeling, and/or forecasting.
• Degree(s) in industrial engineering, electrical engineering, operations research, or a related quantitative field.
• Proficiency in programming (e.g. Python, MATLAB, Julia) and experience with optimisation libraries or forecasting packages.
• Understanding of time series analysis and decision science is highly desirable but not manadatory.
• Excellent communication and writing skills for research dissemination and collaboration.

Scholarships

You may be eligible to apply for a research scholarship.

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Keywords

• forecasting
• optimisation
• machine Learning
• energy
• supply chain

Contact

Contact the supervisor for more information.