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11/11/2022
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization
Bayesian Optimization is a useful tool for experiment design. Unfortunat...
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07/02/2022
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces
Tree ensembles can be well-suited for black-box optimization tasks such ...
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02/10/2022
P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraints
We develop a class of mixed-integer formulations for disjunctive constra...
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02/04/2022
OMLT: Optimization Machine Learning Toolkit
The optimization and machine learning toolkit (OMLT) is an open-source s...
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01/31/2022
SnAKe: Bayesian Optimization with Pathwise Exploration
Bayesian Optimization is a very effective tool for optimizing expensive ...
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01/25/2022
Maximizing information from chemical engineering data sets: Applications to machine learning
It is well-documented how artificial intelligence can have (and already ...
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11/04/2021
Multi-Objective Constrained Optimization for Energy Applications via Tree Ensembles
Energy systems optimization problems are complex due to strongly non-lin...
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02/08/2021
Partition-based formulations for mixed-integer optimization of trained ReLU neural networks
This paper introduces a class of mixed-integer formulations for trained ...
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02/07/2021
Design of Dynamic Experiments for Black-Box Model Discrimination
Diverse domains of science and engineering require and use mechanistic m...
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01/29/2021
Between steps: Intermediate relaxations between big-M and convex hull formulations
This work develops a class of relaxations in between the big-M and conve...
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11/20/2020
Design of Experiments for Verifying Biomolecular Networks
There is a growing trend in molecular and synthetic biology of using mec...
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03/10/2020
ENTMOOT: A Framework for Optimization over Ensemble Tree Models
Gradient boosted trees and other regression tree models perform well in ...
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12/14/2019
Approximating Bounded Job Start Scheduling with Application in Royal Mail Deliveries under Uncertainty
Motivated by mail delivery scheduling problems arising in Royal Mail, we...
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09/26/2019
Approximation Algorithms for Process Systems Engineering
Designing and analyzing algorithms with provable performance guarantees ...
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11/13/2018
Argumentation for Explainable Scheduling (Full Paper with Proofs)
Mathematical optimization offers highly-effective tools for finding solu...
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10/05/2018
GPdoemd: a Python package for design of experiments for model discrimination
Model discrimination identifies a mathematical model that usefully expla...
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05/09/2018
Exact Lexicographic Scheduling and Approximate Rescheduling
In industrial scheduling, an initial planning phase may solve the nomina...
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03/02/2018
Optimization with Gradient-Boosted Trees and Risk Control
Decision trees effectively represent the sparse, high dimensional and no...
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02/12/2018
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches
Healthcare companies must submit pharmaceutical drugs or medical devices...
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12/14/2017
Data Structures for Representing Symmetry in Quadratically Constrained Quadratic Programs
Symmetry in mathematical programming may lead to a multiplicity of solut...
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11/17/2015