Optimising for Impact: Tools and Techniques for Sustainable Decision-Making

This short course explores how mathematical optimisation tools and techniques can be used to support sustainable decision-making aligned with the United Nations Sustainable Development Goals (SDGs). Across five sessions, participants will engage with practical models, algorithms, and tools to address real-world challenges in sustainable supply chains, urban mobility, resource allocation, and resilience planning. Each day combines a lecture on foundational concepts with a hands-on workshop using SageMath, empowering participants to formulate, solve, and interpret optimisation problems in diverse sustainability contexts.
By the end of the course, participants will:

• Understand the role of mathematical optimisation in sustainability.
• Apply optimisation models to problems related to logistics, healthcare, urban planning, and climate resilience.
• Use SageMath to build and analyse diverse decision models.
• Explore the intersection of artificial intelligence and optimisation in sustainable systems.

Topics:

1. Foundations of Optimisation and the UN Sustainable Development Goals (SDG)
2. Sustainable Supply Chains
3. Smart Resource Allocation
4. Resilient and Robust Optimisation under Uncertainty
5. AI Meets Optimisation: Data-Driven Decisions for a Sustainable Future

Relevance

This course will appeal to students, early-career researchers, and professionals in mathematics, engineering, computer science, environmental studies, and related fields who are interested in applying mathematical modelling and optimisation to real-world sustainability challenges. It is particularly relevant for those looking to contribute to data-driven decision-making aligned with the UN Sustainable Development Goals (SDGs).

Pre-requisites

This course is designed to be accessible to participants from diverse disciplinary backgrounds. While no advanced mathematical training is required, participants are expected to have:

• A basic understanding of linear algebra and introductory mathematical modelling concepts
• Familiarity with high school-level algebra and functions (e.g., constraints, optimisation objectives)
• Prior exposure to programming is essential (e.g., Python, MATLAB, R, or similar)
• An interest in applying mathematics to real-world sustainability and decision-making problems

All mathematical concepts will be contextualised within real-world sustainability challenges, and participants will engage in hands-on modelling using SageMath during workshop sessions.

Pre-Reading

1. Introduction to Optimization
   • Chapter 1 of “Convex Optimization” by Stephen Boyd and Lieven Vandenberghe:
     https://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf
2. The UN Sustainable Development Goals (SDGs)
   • The 17 SDGs: https://sdgs.un.org
   • UN SDG Dashboard & Data Explorer: https://unstats.un.org/sdgs/dataportal
3. Introduction to SageMath
   • SageMath “Quickstart”: https://www.sagemath.org/tour-quickstart.html
   • “How to Use SageMath for Linear Programming”:
     https://doc.sagemath.org/html/en/thematic_tutorials/linear_programming.html