OPTIMA ARC
OPTIMA addresses industry's urgent need for decision-making tools to support global competitiveness: reducing lead times and financial and environmental costs while improving efficiency, quality, and agility. Despite strong expertise in academia, industry is yet to fully benefit from optimisation technology due to its high barrier to entry.
OPTIMA works with industry to conduct world-class research and provides training for research students working in industrial optimisation. Connecting industry partners with world-leading interdisciplinary researchers and talented students, OPTIMA will advance an industry-ready optimisation toolkit while training a new generation of industry practitioners and over 120 young researchers, vanguarding a highly skilled workforce of change agents for the transformation of priority sectors including advanced manufacturing, energy resources, and critical infrastructure.
There are no integers in discrete optimisation
Marcella Papini Seminar
Faithful-Newton: a variant of Newton's method for large-scale optimisation
Generating Point Sets of Small Star Discrepancy
Searching for quantum advantage in optimisation: myths, maths, and the travelling salesman problem
Septiana Septiana OPTIMA Student Showreel Competition Winner
From Dense to Sparse: Graphon Mixing for Graph Generation
A Radius Sensitive Approximation Algorithm for Connected Submodular Maximization
Stories of the river: Interpreting and optimising long-term stream monitoring
Particle-based methods for non-convex optimization
Smoothed analysis of the simplex method
Metalearning in Optimisation and Machine Learning
Approximation of functions by neural networks and rational functions
Modelling and analysis of multi-timescale uncertainty in energy system planning
Exact and heuristic solutions for demand management problems in public transport
A Time-expanded Network Exact Algorithm for Solving Escape Interdiction Games
Operationalizing the Rainwater Harvesting Systems: Optimization and Advanced Rule-Based Control
Unlocking the Power of Optimisation: Enhancing Statistical Programs at ABS
Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems
Data-Driven Algorithm Design and Verification for Parametric Convex Optimization
Optimizing the design of wind farms
Automated Planning for Keel Block Reconfiguration at the Captain Cook Graving Dock
Instance Space Analysis for the Quadratic Assignment Problem
A block-building constraint programming model for the container loading problem
Large-State Reinforcement Learning for Hyper-Heuristics
Exact Solutions for k-Steiner Tree Problems
Why Data Science Projects Fail
Gradient-based stochastic optimization under chance constraints
HealthCare Optimisation Hajar Sadegh Zadeh