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Dr Sandy Brownlee

Bibliometrics

Google Scholar (30/11/17)Scopus (30/11/17)
Citations465233
h-index129

Google Scholar author page

Scopus author page

Microsoft academic search author page (for completeness only - see here)

DBLP index

ResearchGate profile

ORCID ID 0000-0003-2892-5059

Wherever possible, in addition to the publisher record, I've provided links to the preprint or open access versions of articles below. If you are having trouble accessing any of my papers, please contact me by clicking my name at the foot of this page.

Publications - peer reviewed journals

  1. Brownlee, A. E. I., Burles, N. and Swan, J. (2017) Search-based energy optimization of some ubiquitous algorithms. IEEE Transactions on Emerging Topics in Computational Intelligence, vol 1, issue 3, pp. 188-201. DOI:10.1109/TETCI.2017.2699193 (open access at publisher)
  2. Benlic, U., Brownlee, A. E. I. and Burke, E.K. (2016) Heuristic search for the coupled runway sequencing and taxiway routing problem. Transportation Research Part C: Emerging Technologies, vol 71, pp.333-355. DOI:10.1016/j.trc.2016.08.004 (open access at publisher)
  3. Wang, M., Wright, J. A., Brownlee, A. E. I. and Buswell, R.A. (2016) A comparison of approaches to stepwise regression on variables sensitivities in building simulation and analysis. Energy and Buildings, vol 127, pp.313-326. DOI:10.1016/j.enbuild.2016.05.065 (preprint available via Stirling repository)
  4. Brownlee, A. E. I. and Wright, J. A. (2015) Constrained, mixed-integer and multi-objective optimisation of building designs by NSGA-II with fitness approximation. Applied Soft Computing, vol.33, pp 114-126. DOI:10.1016/j.asoc.2015.04.010 (open access at publisher)
  5. McKinstray, R., Lim, J. B., Tanyimboh, T. T., Phan, D. T., Sha, W., Brownlee, A. E (2014). Topographical optimisation of single-storey non-domestic steel framed buildings using photovoltaic panels for net-zero carbon impact. Building and Environment, vol. 86, pp.120-131. DOI:10.1016/j.buildenv.2014.12.017 (preprint available via Stirling repository)
  6. Wright, J.A.W., Brownlee, A.E.I., Mourshed, M.M., Wang, M. (2014). Multi-objective Optimization of Cellular Fenestration by an Evolutionary Algorithm, Journal of Building Performance Simulation, vol.7, issue 1, pp.33-51. DOI:10.1080/19401493.2012.762808 (preprint available via Loughborough repository)
  7. Brownlee, A.E.I., McCall, J.A.W., Zhang, Q (2013). Fitness Modelling with Markov Networks, IEEE Transactions on Evolutionary Computation, vol.17, issue 6, pp. 862-879. DOI:10.1109/TEVC.2013.2281538
  8. Brownlee, A. E. I., Regnier-Coudert, O., McCall, J. A. W., Massie, S. & Stulajter, S. (2013). An application of a GA with Markov network surrogate to feature selection, International Journal of Systems Science, vol. 44, issue 11, pp.2039-2056. DOI:10.1080/00207721.2012.684449

Publications - peer reviewed book chapters

  1. Shakya, S. K., McCall, J. A. W., Brownlee, A. E. I. & Owusu, G. (2012). DEUM - Distribution Estimation Using Markov Networks, in: Shakya, S. K. and Santana, R., Markov Networks in Evolutionary Computation. pp. 55-71. Springer. (invited book chapter) DOI:10.1007/978-3-642-28900-2_4
  2. Brownlee, A. E. I., McCall, J. A. W. & Shakya, S. K. (2012). The Markov Network Fitness Model, in: Shakya, S. K. and Santana, R., Markov Networks in Evolutionary Computation. pp. 125-140. Springer. (invited book chapter) DOI:10.1007/978-3-642-28900-2_8
  3. McCall, J. A. W., Brownlee, A. E. I. & Shakya, S. K. (2012). Applications of Distribution Estimation Using Markov Network Modelling (DEUM), in: Shakya, S. K. and Santana, R., Markov Networks in Evolutionary Computation. pp. 193-207. Springer. (invited book chapter) DOI:10.1007/978-3-642-28900-2_12
  4. Brownlee, A. E. I., McCall, J. A. W., Shakya, S. K. & Zhang, Q. (2009). Structure Learning and Optimisation in a Markov-network based Estimation of Distribution Algorithm. (extended version of earlier conference paper) Invited book chapter in "Chen, Y (ed.) Exploitation of Linkage Learning in Evolutionary Algorithms", Springer 2010. ISBN 978-3-642-12834-9
  5. Shakya, S. K., Brownlee, A. E. I., McCall, J. A. W., Fournier, F. & Owusu, G. (2009). A fully multivariate DEUM algorithm. (extended version of earlier conference paper) Invited book chapter in "Chen, Y (ed.) Exploitation of Linkage Learning in Evolutionary Algorithms", Springer 2010. ISBN 978-3-642-12834-9

Publications - peer reviewed conferences

  1. Adair, J., Brownlee, A.E.I, Daolio, F., & Ochoa, G. Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces. MOD 2017 - The Third International Conference on Machine Learning, Optimization and Big Data.
  2. Haraldsson, S.O., Woodward, J.R., Brownlee, A. E. I., Smith, A.V. & Gudnason, V. FGenetic Improvement of Runtime in a Bioinformatics Application. Genetic Improvement Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2017, Berlin, Germany. Accepted, to appear
  3. Haraldsson, S.O., Woodward, J.R., Brownlee, A. E. I. & Siggeirsdottir, K. Fixing Bugs in Your Sleep: How Genetic Improvement Became an Overnight Success. Genetic Improvement Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2017, Berlin, Germany. Accepted, to appear
  4. Haraldsson, S.O., Woodward, J.R. and Brownlee, A.E.I. The Use of Automatic Test Data Generation for Genetic Improvement in a Live System. Search-Based Software Testing Workshop in: IEEE/ACM International Conference on Software Engineering 2017, Buenos Ares, Argentina. Accepted, to appear
  5. Haraldsson, S.O., Woodward, J.R., Brownlee, A.E.I. and Cairns, D.E. Exploring Fitness and Edit Distance of Mutated Python Programs. In: Proc. EuroGP 2017, Amsterdam, Netherlands. Accepted, to appear
  6. Adair, J., Brownlee, A. and Ochoa, G. Evolutionary Algorithms with Linkage Information for Feature Selection in Brain Computer Interfaces. In: Proc. UK Workshop on Computational Intelligence 2016. DOI:10.1007/978-3-319-46562-3_19 (preprint available via Stirling repository)
  7. Brownlee, A. E. I. Mining Markov Network Surrogates for Value Added Optimisation. Surrogate Assisted Evolutionary Optimisation (SAEOpt) Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2016, Denver, CO, USA. DOI:10.1145/2908961.2931711 - slides (preprint available via Stirling repository)
  8. Woodward, J.R., Johnson, C.G, & Brownlee, A. E. I. Connecting automatic parameter tuning, genetic programming as a hyper-heuristic and genetic improvement programming. Evolutionary Computation for the Automated Design of Algorithms (ECADA) Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2016, Denver, CO, USA. DOI:10.1145/2908961.2931728 (preprint available here)
  9. Woodward, J.R., Brownlee, A. E. I. & Johnson, C.G. Evals is not enough: why we should report wall-clock time. Genetic Improvement Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2016, Denver, CO, USA. DOI:10.1145/2908961.2931695 (preprint available via Stirling repository)
  10. Woodward, J.R., Johnson, C.G, & Brownlee, A. E. I. GP vs GI: if you can't beat them, join them. Genetic Improvement Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2016, Denver, CO, USA. DOI:10.1145/2908961.2931694 (preprint available via Stirling repository)
  11. He, M., Brownlee, A. E. I., Wright, J. A., Taylor, S. C. Multi-dwelling Refurbishment Optimization: Problem Decomposition, Solution, and Trade-off Analysis. Proc. IBPSA Building Simulation Conference 2015, Hyderabad, India. pp.2066-2072. Paper
  12. Burles, N., Bowles, E., Brownlee, A.E.I., Kocsis, Z., Swan, J. and Veerapen, N. Object-Oriented Genetic Improvement for Improved Energy Consumption in Google Guava. Proc. SSBSE Challenge Track 2015, Bergamo, Italy. LNCS 9275. pp. 255-261. Springer. DOI:10.1007/978-3-319-22183-0_20 (preprint available via Stirling repository)
  13. Kocsis, Z., Brownlee, A., Swan, J., Senington, R. Haiku - a Scala combinator toolkit for semi-automated composition of metaheuristics. Proc. SSBSE 2015, Bergamo, Italy. LNCS 9275. pp. 125-140. Springer. DOI:10.1007/978-3-319-22183-0_9 (preprint available via Stirling repository)
  14. He, M., Lee, T., Taylor, S. C., Brownlee, A. E. I., Wright, J. A. Multi-objective optimization for a large scale retrofit program for the housing stock in the North East of England. 6th International Building Physics Conference, IBPC 2015, Turin, Italy. Energy Procedia vol. 78, November 2015, pp. 854-859. DOI: 10.1016/j.egypro.2015.11.007 (preprint available via Stirling repository)
  15. Brownlee, A. E. I., Woodward, J.R. and Swan, J. Metaheuristic Design Pattern: Surrogate Fitness Functions. MetaDeeP Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2015, Madrid, Spain. pp.1261-1264. ACM Press. DOI:10.1145/2739482.2768499 Slides (preprint available via Stirling repository)
  16. Swan, J., Bowles, E., Burles, N., Brownlee, A. E. I., Kocsis, Z.A. and Veerapen, N. Embedded Dynamic Improvement Programming. Genetic Improvement Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2015, Madrid, Spain. pp.831-832. ACM Press.
  17. Brownlee, A. E. I., McCall, J. A. W., and Christie, Lee A. Structural Coherence of Problem and Algorithm: An Analysis for EDAs on all 2-bit and 3-bit Problems. Proc. of the Congress on Evolutionary Computation 2015, Sendai, Japan. pp.2066-2073. IEEE Press. (Nominated for best paper)
  18. Kocsis, Z., Neumann, G., Swan, J., Epitropakis, M., Brownlee, A., Haraldsson, S. and Bowles, E. Repairing and optimizing Hadoop hashCode implementations. Proc. SSBSE Challenge Track, Fortaleza, Brazil. pp.259-264. Springer, 2014. (full text on ResearchGate)
  19. Brownlee, A. E. I., Swan, J., Özcan, E. and Parkes, A. J. Hyperion2 - A toolkit for {meta-, hyper-} heuristic research. EvoSoft Workshop in: Companion Proc. of the Genetic and Evolutionary Computation COnference 2014, Vancouver, BC, Canada. pp.1133-1140. ACM Press.
  20. Wang, M., Wright, J., Brownlee, A., and Buswell, R. A Comparison of Approaches to Stepwise Regression Analysis for Variables Sensitivity Measurements Used with a Multi-Objective Optimization Problem. Proc. ASHRAE 2014 Annual Conf., Seattle, WA, 2014.
  21. Wang, M., Wright, J., Brownlee, A., and Buswell, R. Applying Global and Local SA in Identification of Variables Importance with the use of Multi-Objective Optimization. Proc. 2nd IBPSA-England Building Simulation and Optimization Conf., 2014.
  22. Watson, V., Jones, E., Murphy, E., Wright, J., Brownlee, A. and Aird, G. (2013). Industry challenges in using optimisation tools with IES Optimise as a case study. CIBSE Technical Symposium, Liverpool John Moores University, Liverpool, UK.
  23. Wang, M., Wright, J., Brownlee, A., and Buswell, R. A comparison of approaches to stepwise regression for global sensitivity analysis used with evolutionary optimization. Pro. 13th Int. IBPSA Conf., 2013, 2551-2558.
  24. Brownlee, A. E. I. and Wright, J. A. (2012). Solution Analysis in Multi-Objective Optimization. Building Simulation and Optimization Conference, Loughborough, UK, pp.317-324. IBPSA England.
  25. Wright, J. A. W., Wang, M., Brownlee, A. E. I. & Buswell, R. A. (2012). Variable Convergence in Evolutionary Optimization and its Relationship to Sensitivity Analysis, Building Simulation and Optimization Conference, Loughborough, UK, pp. 102-109. IBPSA England.
  26. Brownlee, A. E. I., McCall, J. A. W., Pelikan, M. (2012). Influence of selection on structure learning in markov network EDAs: an empirical study., Proc. of the Genetic and Evolutionary Computation COnference 2012, Philadelphia, PA, USA, pp. 249-256. ACM Press.
  27. Brownlee, A. E. I., Wright, J. A. & Mourshed, M. M. (2011). A multi-objective window optimisation problem, Proc. of the Genetic and Evolutionary Computation COnference 2011, Dublin, ROI, pp. 89-90. ACM Press.
  28. Brownlee, A. E. I., Regnier-Coudert, O., McCall, J. A. W. & Massie, S. (2010). Using a Markov Network as a Surrogate Fitness Function in a Genetic Algorithm, Proc. of the Congress on Evolutionary Computation 2010, Barcelona, Spain, pp. 4525-4532. IEEE Press.
  29. Brownlee, A. E. I., McCall, J. A. W., Shakya, S. K. & Zhang, Q. (2009). Structure Learning and Optimisation in a Markov-network based Estimation of Distribution Algorithm, Proc. of the Congress on Evolutionary Computation 2009, Trondheim, Norway, pp. 447-454. IEEE Press.
  30. Shakya, S. K., Brownlee, A. E. I., McCall, J. A. W., Fournier, F. & Owusu, G. (2009). A fully multivariate DEUM algorithm, Proc. of the Congress on Evolutionary Computation 2009, Trondheim, Norway, pp. 479-486. IEEE Press.
  31. Brownlee, A. E. I., Wu, Y., McCall, J. A. W., Godley, P. M., Cairns, D. E. & Cowie, J. (2008). Optimisation and fitness modelling of bio-control in mushroom farming using a Markov network EDA, Proc. of the Genetic and Evolutionary Computation COnference 2008, Atlanta, Georgia, USA, pp. 465-466. ACM Press.
  32. Brownlee, A. E. I., Pelikan, M., McCall, J. A.W. & Petrovski, A. (2008). An application of a multivariate estimation of distribution algorithm to cancer chemotherapy, Proc. of the Genetic and Evolutionary Computation COnference 2008, Atlanta, Georgia, USA, pp. 463-464. ACM Press.
  33. Brownlee, A. E. I., McCall, J. A. W., Zhang, Q. & Brown, D. (2008). Approaches to Selection and their Effect on Fitness Modelling in an Estimation of Distribution Algorithm, Proc. of the World Congress on Computational Intelligence 2008, Hong Kong, China, pp. 2621-2628. IEEE Press.
  34. Wu, Y., McCall, J., Godley, P., Brownlee, A. & Cairns, D. (2008). Bio-control in mushroom farming using a Markov network EDA, Proc. of the World Congress on Computational Intelligence 2008, Hong Kong, China, pp. 2996-3001. IEEE Press.
  35. Petrovski, A., Brownlee, A. and McCall, J. (2005). Statistical optimisation and tuning of GA factors, Proc. of the Congress on Evolutionary Computation 2005, Edinburgh, UK, pp. 758-764. IEEE Press.

Publications - other

  1. Haraldsson, S.O., Brownlee, A.E.I. and Woodward, J.R. (2017). Computers will soon be able to fix themselves - are IT departments for the chop?, The Conversation.
  2. Brownlee, A.E.I. and Swan, J. (2017). Never mind the iPhone X, battery life could soon take a great leap forward, The Conversation.
  3. Brownlee, A.E.I. and Woodward, J.R. Why we fell out of love with algorithms inspired by nature, The Conversation.
  4. McCall, J.A.W., Christie, L.A. and Brownlee, A.E.I. (2015). Generating Easy and Hard Problems using the Proximate Optimality Principle, Proc. of the Genetic and Evolutionary Computation COnference 2015, Madrid, Spain, Late Breaking Papers. pp.767-768 ACM Press.
  5. Brownlee, A.E.I., Benlic, U. and Burke, E.K. (2014). Air traffic control about to let pilots plan their own routes - but don't worry, The Conversation.
  6. Brownlee, A.E.I., Atkin, J.A.D., Woodward, J.R., Benlic, U. and Burke, E.K. (2014). Airport Ground Movement: Real World Data Sets and Approaches to Handling Uncertainty, Proc. of the Practice and Theory of Automated Timetabling (PATAT) Conference, York, UK, pp. 462-464. Extended abstract for presentation. Abstract | Slides
  7. Brownlee, A.E.I. (2009). Multivariate Markov networks for fitness modelling in an estimation of distribution algorithm. PhD Thesis, Robert Gordon University, UK.
  8. Brownlee, A.E.I., McCall, J.A.W. and Brown, D.F. (2007). Solving the MAXSAT Problem using a Multivariate EDA based on Markov Networks, Proc. of the Genetic and Evolutionary Computation COnference 2007, London, UK, Late Breaking Papers. ACM Press.
  9. Brownlee, A.E.I. (2005). An Application of Genetic Algorithms to University Timetabling, undergraduate honours project report, Robert Gordon University, UK. Related presentation slides here.

Seminars, Presentations and External Invited Talks

An Overview of Artificial Intelligence - talk given to Stirling Probus Club, 25 October 2017

Planes, training and optimobiles: adding value to optimisation in the real world - Univ. of Stirling, 29 September 2017 - slides

Funding Hints and Tips from the EPSRC - COSMOS talk - slides

A whistle-stop tour of LaTeX - COSMOS talk, joint with Nada Veerapen - slides pt 1 and slides pt 2

Hyper-parameter tuning to improve existing software - invited talk at the 50th Crest Open Workshop (on Genetic Improvement), UCL, London, 31 January 2017 - slides - talk (480p) (720p)

Adding value to optimisation by interrogating fitness models - presentation at Model Based Evolutionary Algorithms workshop, GECCO, 20 July 2016 - slides

Weighing up the options: Finding the right solution when lots of things matter - Public lecture, Univ. of Stirling, 17 March 2016 - slides.

Airport ground movement: Real world data sets and approaches to handling uncertainty - LANCS workshop on Air Transportation at Univ. of Nottingham - slides available on linked page

Fitness modelling for better optimisation and decision making - Univ. of Stirling, 29 Sept 2013 - slides

Multi-objective Optimisation of Building Designs - Robert Gordon University, 9 Dec 2011 - slides

Markov Networks & Fitness Modelling in Evolutionary Algorithms - Univ. of Stirling, 17 Oct 2008

Author-izer links to articles published by ACM

ACM DL Author-ize serviceMining Markov Network Surrogates for Value-Added Optimisation
Alexander E.I. Brownlee
GECCO '16 Companion Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016
ACM DL Author-ize serviceEvals is Not Enough: Why We Should Report Wall-clock Time
John R. Woodward, Alexander E.I. Brownlee, Colin G. Johnson
GECCO '16 Companion Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016
ACM DL Author-ize serviceGP vs GI: If You Can't Beat Them, Join Them
John R. Woodward, Colin G. Johnson, Alexander E.I. Brownlee
GECCO '16 Companion Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016
ACM DL Author-ize serviceConnecting Automatic Parameter Tuning, Genetic Programming as a Hyper-heuristic, and Genetic Improvement Programming
John R. Woodward, Colin G. Johnson, Alexander E.I. Brownlee
GECCO '16 Companion Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016
ACM DL Author-ize serviceGenerating Easy and Hard Problems using the Proximate Optimality Principle
John A.W. McCall, Lee A. Christie, Alexander E.I. Brownlee
GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
ACM DL Author-ize serviceEmbedded Dynamic Improvement
Nathan Burles, Jerry Swan, Edward Bowles, Alexander E.I. Brownlee, Zoltan A. Kocsis, Nadarajen Veerapen
GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
ACM DL Author-ize serviceMetaheuristic Design Pattern: Surrogate Fitness Functions
Alexander E.I. Brownlee, John R. Woodward, Jerry Swan
GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
ACM DL Author-ize serviceHyperion2: a toolkit for {meta-, hyper-} heuristic research
Alexander E.I. Brownlee, Jerry Swan, Ender Özcan, Andrew J. Parkes
GECCO Comp '14 Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation, 2014
ACM DL Author-ize serviceInfluence of selection on structure learning in markov network EDAs: an empirical study
Alexander E.I. Brownlee, John A.W. McCall, Martin Pelikan
GECCO '12 Proceedings of the 14th annual conference on Genetic and evolutionary computation, 2012
ACM DL Author-ize serviceA multi-objective window optimisation problem
Alexander E.I. Brownlee, Jonathan A. Wright, Monjur M. Mourshed
GECCO '11 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
ACM DL Author-ize serviceSolving the MAXSAT problem using a multivariate EDA based on Markov networks
Alexander E. I. Brownlee, John A. W. McCall, Deryck F. Brown
GECCO '07 Proceedings of the 9th annual conference companion on Genetic and evolutionary computation, 2007