Richard Allmendinger
Richard Allmendinger
Professor at The University of Manchester, UK, Fellow of the Alan Turing Institute
Verified email at - Homepage
Cited by
Cited by
Surrogate‐assisted multicriteria optimization: Complexities, prospective solutions, and business case
R Allmendinger, MTM Emmerich, J Hakanen, Y Jin, E Rigoni
Journal of Multi‐Criteria Decision Analysis 24 (1-2), 5-24, 2017
Efficient discovery of anti-inflammatory small-molecule combinations using evolutionary computing
BG Small, BW McColl, R Allmendinger, J Pahle, G López-Castejón, ...
Nature chemical biology 7 (12), 902-908, 2011
Life‐cycle and cost of goods assessment of fed‐batch and perfusion‐based manufacturing processes for mAbs
P Bunnak, R Allmendinger, SV Ramasamy, P Lettieri, ...
Biotechnology progress 32 (5), 1324-1335, 2016
Multiobjective optimization: When objectives exhibit non-uniform latencies
R Allmendinger, J Handl, J Knowles
European Journal of Operational Research 243 (2), 497-513, 2015
Constraint handling in efficient global optimization
S Bagheri, W Konen, R Allmendinger, J Branke, K Deb, J Fieldsend, ...
Proceedings of the genetic and evolutionary computation conference, 673-680, 2017
Reference point-based particle swarm optimization using a steady-state approach
R Allmendinger, X Li, J Branke
Simulated Evolution and Learning: 7th International Conference, SEAL 2008 …, 2008
A feature rich distance-based many-objective visualisable test problem generator
JE Fieldsend, T Chugh, R Allmendinger, K Miettinen
Proceedings of the Genetic and Evolutionary Computation Conference, 541-549, 2019
Closed‐loop optimization of chromatography column sizing strategies in biopharmaceutical manufacture
R Allmendinger, AS Simaria, R Turner, SS Farid
Journal of Chemical Technology & Biotechnology 89 (10), 1481-1490, 2014
‘Hang on a minute’: investigations on the effects of delayed objective functions in multiobjective optimization
R Allmendinger, J Knowles
Evolutionary Multi-Criterion Optimization: 7th International Conference, EMO …, 2013
Navigation in multiobjective optimization methods
R Allmendinger, M Ehrgott, X Gandibleux, MJ Geiger, K Klamroth, ...
Journal of Multi‐Criteria Decision Analysis 24 (1-2), 57-70, 2017
Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies
T Chugh, R Allmendinger, V Ojalehto, K Miettinen
Proceedings of the genetic and evolutionary computation conference, 609-616, 2018
On handling ephemeral resource constraints in evolutionary search
R Allmendinger, J Knowles
Evolutionary computation 21 (3), 497-531, 2013
Multiobjective evolutionary optimization in antibody purification process design
R Allmendinger, AS Simaria, SS Farid
Biochemical engineering journal 91, 250-264, 2014
Tuning evolutionary search for closed-loop optimization
R Allmendinger
PQDT-UK & Ireland, 2012
Transfer learning based surrogate assisted evolutionary bi-objective optimization for objectives with different evaluation times
X Wang, Y Jin, S Schmitt, M Olhofer, R Allmendinger
Knowledge-Based Systems 227, 107190, 2021
Dynamic scheduling of multi-product continuous biopharmaceutical facilities: A hyper-heuristic framework
FB Oyebolu, R Allmendinger, SS Farid, J Branke
Computers & Chemical Engineering 125, 71-88, 2019
Safe learning and optimization techniques: Towards a survey of the state of the art
Y Kim, R Allmendinger, M López-Ibáñez
Trustworthy AI-Integrating Learning, Optimization and Reasoning: First …, 2021
Heterogeneous objectives: state-of-the-art and future research
R Allmendinger, J Knowles
arXiv preprint arXiv:2103.15546, 2021
Evolving controllably difficult datasets for clustering
C Shand, R Allmendinger, J Handl, A Webb, J Keane
Proceedings of the Genetic and Evolutionary Computation Conference, 463-471, 2019
Evolutionary optimization on problems subject to changes of variables
R Allmendinger, J Knowles
Parallel Problem Solving from Nature, PPSN XI: 11th International Conference …, 2010
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