23 citations · 89 across the 19 of their papers we have counts for
10 papers · 1 filter
A Study of Scalarisation Techniques for Multi-Objective QUBO Solving
Mayowa Ayodele, Richard Allmendinger, Manuel López-Ibáñez +1
In recent years, there has been significant research interest in solving Quadratic Unconstrained Binary Optimisation (QUBO) problems. Physics-inspired optimisation algorithms have…
Comparing the Utility and Disclosure Risk of Synthetic Data with Samples of Microdata
Claire Little, Mark Elliot, Richard Allmendinger
Most statistical agencies release randomly selected samples of Census microdata, usually with sample fractions under 10% and with other forms of statistical disclosure control (SDC…
Combining Topic Modeling with Grounded Theory: Case Studies of Project Collaboration
Eyyub Can Odacioglu, Lihong Zhang, Richard Allmendinger
This paper proposes an Artificial Intelligence (AI) Grounded Theory for management studies. We argue that this novel and rigorous approach that embeds topic modelling will lead to…
Cooperative Multi-Agent Search on Endogenously-Changing Fitness Landscapes
Chin Woei Lim, Richard Allmendinger, Joshua Knowles +2
We use a multi-agent system to model how agents (representing firms) may collaborate and adapt in a business 'landscape' where some, more influential, firms are given the power to…
Efficient Approximation of Expected Hypervolume Improvement using Gauss-Hermite Quadrature
Alma Rahat, Tinkle Chugh, Jonathan Fieldsend +2
Many methods for performing multi-objective optimisation of computationally expensive problems have been proposed recently. Typically, a probabilistic surrogate for each objective…
Detection of Hidden Objectives and Interactive Objective Reduction
Seyed Mahdi Shavarani, Manuel López-Ibáñez, Richard Allmendinger
In multi-objective optimization problems, there might exist hidden objectives that are important to the decision-maker but are not being optimized. On the other hand, there might a…
Multi-objective QUBO Solver: Bi-objective Quadratic Assignment
Mayowa Ayodele, Richard Allmendinger, Manuel López-Ibáñez +1
Quantum and quantum-inspired optimisation algorithms are designed to solve problems represented in binary, quadratic and unconstrained form. Combinatorial optimisation problems are…
A Data-Driven Framework for Identifying Investment Opportunities in Private Equity
Samantha Petersone, Alwin Tan, Richard Allmendinger +2
The core activity of a Private Equity (PE) firm is to invest into companies in order to provide the investors with profit, usually within 4-7 years. To invest into a company or not…
Are Evolutionary Algorithms Safe Optimizers?
Youngmin Kim, Richard Allmendinger, Manuel López-Ibáñez
We consider a type of constrained optimization problem, where the violation of a constraint leads to an irrevocable loss, such as breakage of a valuable experimental resource/platf…
SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms
Tasos Asonitis, Richard Allmendinger, Matt Benatan +1
We propose SonOpt, the first (open source) data sonification application for monitoring the progress of bi-objective population-based optimization algorithms during search, to faci…