13 citations · 31 across the 8 of their papers we have counts for
9 papers
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…
Towards a fairer reimbursement system for burn patients using cost-sensitive classification
Chimdimma Noelyn Onah, Richard Allmendinger, Julia Handl +1
The adoption of the Prospective Payment System (PPS) in the UK National Health Service (NHS) has led to the creation of patient groups called Health Resource Groups (HRG). HRGs aim…
What if we Increase the Number of Objectives? Theoretical and Empirical Implications for Many-objective Optimization
Richard Allmendinger, Andrzej Jaszkiewicz, Arnaud Liefooghe +1
The difficulty of solving a multi-objective optimization problem is impacted by the number of objectives to be optimized. The presence of many objectives typically introduces a num…