Efficient formulation and solution methods

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming
Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability …
PDF Cite DOI
ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming
Input convex neural networks as surrogates in mathematical optimisation
Embedding trained neural networks as surrogates within optimisation problems is an established practice in operations research. The …
PDF Cite DOI
Input convex neural networks as surrogates in mathematical optimisation
A Robust Optimization Approach to Flow Decomposition
In this paper, we generalize the minimum flow decomposition problem (MFD) to incorporate uncertain edge capacities and tackle it from …
PDF Cite DOI
A Robust Optimization Approach to Flow Decomposition
Decision tree enhancer (DTE): Improving decision trees with optimization
Decision trees are off-the-shelf machine learning models widely used for classification and regression tasks in medical, logistics, …
PDF Cite DOI
Decision tree enhancer (DTE): Improving decision trees with optimization
An efficient mixed-integer linear programming formulation for solving influence diagrams
Influence diagrams represent decision-making problems with interdependencies between random events, decisions, and consequences. …
PDF Cite Project DOI
An efficient mixed-integer linear programming formulation for solving influence diagrams
Solving Influence Diagrams: Efficient Mixed-Integer Programming Formulation and Heuristic
In this paper, we propose novel mixed-integer linear programming (MIP) formulations to model decision problems posed as influence …
PDF Cite Project DOI
Solving Influence Diagrams: Efficient Mixed-Integer Programming Formulation and Heuristic
Simulator-based surrogate optimisation employing adaptive uncertainty-aware sampling
Optimisation problems involving computationally expensive, black-box functions derived from high-fidelity engineering simulations …
PDF Cite DOI
Simulator-based surrogate optimisation employing adaptive uncertainty-aware sampling
Solving decision problems with endogenous uncertainty and conditional information revelation using influence diagrams
Mathematical programming formulations of influence diagrams can bridge the gap between representing and solving decision problems. …
PDF Cite Project DOI
Solving decision problems with endogenous uncertainty and conditional information revelation using influence diagrams
Employing federated learning for training autonomous HVAC systems
Buildings account for 40 % of global energy consumption. A considerable portion of building energy consumption stems from heating, …
PDF Cite Project DOI
Employing federated learning for training autonomous HVAC systems
Streamlining emergency response: A K-adaptable model and a column-and-constraint-generation algorithm
Emergency response refers to the systematic response to an unexpected, disruptive occurrence such as a natural disaster. The response …
PDF Cite DOI
Streamlining emergency response: A K-adaptable model and a column-and-constraint-generation algorithm