Publications

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  • K. Smith-Miles, J Christiansen, MA Muñoz, M. Munoz Acosta. Revisiting where are the hard knapsack problems? via Instance Space Analysis. Computers and Operations Research, 128, 105184 (18pp), 2021. doi: 10.1016/j.cor.2020.105184.

  • Luiz Henrique dos Santos Fernandes, Ana Carolina Lorena, K. Smith-Miles. Towards Understanding Clustering Problems and Algorithms: An Instance Space Analysis. Algorithms, 14, 95 (29pp), 2021. doi: 10.3390/a14030095.

  • Mario Andrés Muñoz, Tao Yan, Matheus R Leal, K. Smith-Miles, Ana Carolina Lorena, Gisele L Pappa, Rômulo Madureira Rodrigues, M. Munoz Acosta. An Instance Space Analysis of Regression Problems. ACM Transactions on Knowledge Discovery from Data, 15, 1-25, 2021. doi: 10.1145/3436893.

  • M. FOUMANI, A Razeghi, K. Smith-Miles. Stochastic optimization of two-machine flow shop robotic cells with controllable inspection times: From theory toward practice. Robotics and Computer-Integrated Manufacturing, 61, 101822 (20pp), 2020. doi: 10.1016/j.rcim.2019.101822.

  • P Baniasadi, M. FOUMANI, K. Smith-Miles, V Ejov. A transformation technique for the clustered generalized traveling salesman problem with applications to logistics. European Journal of Operational Research, 444-457, 2020. doi: 10.1016/j.ejor.2020.01.053.

  • B Abbasi, T Babaei, Z Hosseinifard, K. Smith-Miles, M Dehghani. Predicting solutions of large-scale optimization problems via machine learning: A case study in blood supply chain management. Computers and Operations Research, 119, 104941 (20pp), 2020. doi: 10.1016/j.cor.2020.104941.

  • Mark B Flegg, Mario A Munoz, K. Smith-Miles, Wai Shan Yuen, John G Carroll, Mario A Muñoz, M. Munoz Acosta. Parameter estimation for a point-source diffusion-decay morphogen model.. Journal of mathematical biology, 2227-2255, 2020. doi: 10.1007/s00285-020-01494-x.

  • Lucas Kletzander, Nysret Musliu, K. Smith-Miles. Instance space analysis for a personnel scheduling problem. Annals of Mathematics and Artificial Intelligence, 1-21, 2020. doi: 10.1007/s10472-020-09695-2.

  • E Yap, MA Munoz, K. Smith-Miles, A Liefooghe, M. Munoz Acosta. Instance Space Analysis of Combinatorial Multi-objective Optimization Problems. 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings, 1-8, 2020. doi: 10.1109/CEC48606.2020.9185664.

  • Priyanga Dilini Talagala, Rob J Hyndman, K. Smith-Miles. Anomaly Detection in High-Dimensional Data. Journal of Computational and Graphical Statistics, 360-374, 2020. doi: 10.1080/10618600.2020.1807997.

  • Sevvandi Kandanaarachchi, Rob J Hyndman, K. Smith-Miles. Early classification of spatiooral events using partial information. PloS one, 15, e0236331 (39pp), 2020. doi: 10.1371/journal.pone.0236331.

  • K. Smith-Miles, X. GENG. Revisiting Facial Age Estimation with New Insights from Instance Space Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1, 2020. doi: 10.1109/TPAMI.2020.3038760.

  • M. FOUMANI, K. Smith-Miles. The impact of various carbon reduction policies on green flowshop scheduling. Applied Energy, 249, 300-315, 2019. doi: 10.1016/j.apenergy.2019.04.155.

  • Mario A Muñoz, K. Smith-Miles, M. Munoz Acosta. Generating New Space-Filling Test Instances for Continuous Black-Box Optimization.. Evolutionary computation, 379-404, 2019. doi: 10.1162/evco_a_00262.

  • Priyanga Dilini Talagala, Rob J Hyndman, K. Smith-Miles, Sevvandi Kandanaarachchi, Mario A Munoz, MA Muñoz, M. Munoz Acosta. Anomaly Detection in Streaming Nonstationary Temporal Data. Journal of Computational and Graphical Statistics, 13-27, 2019. doi: 10.1080/10618600.2019.1617160.

  • S Kandanaarachchi, MA Muñoz, RJ Hyndman, K. Smith-Miles, M. Munoz Acosta. On normalization and algorithm selection for unsupervised outlier detection. Data Mining and Knowledge Discovery, 309-354, 2019. doi: 10.1007/s10618-019-00661-z.

  • S Kandanaarachchi, MA Muñoz, K. Smith-Miles, M. Munoz Acosta. Instance space analysis for unsupervised outlier detection. CEUR Workshop Proceedings, 2436, 2019.

  • Conrad Chan, Aldeida Aleti, Alexander Heger, K. Smith-Miles. Evolving stellar models to find the origins of our galaxy. Proceedings of the Genetic and Evolutionary Computation Conference, 1129-1137, 2019. doi: 10.1145/3321707.3321714.

  • S. EDWARDS, Davaatseren Baatar, K. Smith-Miles, Andreas T Ernst. Symmetry breaking of identical projects in the high-multiplicity RCPSP/max. Journal of the Operational Research Society, 1-22, 2019. doi: 10.1080/01605682.2019.1595192.

  • S Bowly, K. Smith-Miles, D Baatar, H Mittelmann. Generation techniques for linear programming instances with controllable properties. Mathematical Programming Computation, 389-415, 2019. doi: 10.1007/s12532-019-00170-6.

  • Priyanga Dilini Talagala, Rob J Hyndman, Catherine Leigh, Kerrie Mengersen, K. Smith-Miles, Kate Smith‐Miles. A Feature‐Based Procedure for Detecting Technical Outliers in Water‐Quality Data From In Situ Sensors. Water Resources Research, 55, 8547-8568, 2019. doi: 10.1029/2019WR024906.

  • Simon Andrew Bowly, K. Smith-Miles. Stress testing mixed integer programming solvers through new test instance generation methods. 2019.

  • M Foumani, A. Moeini, M Haythorpe, K. Smith-Miles. A cross-entropy method for optimising robotic automated storage and retrieval systems. International Journal of Production Research, 6450-6472, 2018. doi: 10.1080/00207543.2018.1456692.

  • Mario A Munoz, Laura Villanova, D. Baatar, K. Smith-Miles, MA Muñoz. Instance spaces for machine learning classification. Machine Learning, 107, 109-147, 2018. doi: 10.1007/s10994-017-5629-5.

  • R Lewis, K. Smith-Miles, K Phillips. The school bus routing problem: An analysis and algorithm. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10765 LNCS, 287-298, 2018. doi: 10.1007/978-3-319-78825-8_24.

  • C Oliveira, A Aleti, L Grunske, K. Smith-Miles. Mapping the Effectiveness of Automated Test Suite Generation Techniques. IEEE Transactions on Reliability, 771-785, 2018. doi: 10.1109/TR.2018.2832072.

  • R Lewis, K. Smith-Miles. A heuristic algorithm for finding cost-effective solutions to real-world school bus routing problems. Journal of Discrete Algorithms, 2-17, 2018. doi: 10.1016/j.jda.2018.11.001.

  • Carolina Segovia Riquelme, K. Smith-Miles, C Segovia. Integrating Game Theory and Data Mining for Dynamic Distribution of Police to Combat Crime. Proceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018, 780-783, 2018. doi: 10.1109/WI.2018.00016.

  • Mehdi Foumani, K. Smith-Miles, Indra Gunawan, A. Moeini. A framework for stochastic scheduling of two-machine robotic rework cells with in-process inspection system. Computers and Industrial Engineering, 112, 492-502, 2017. doi: 10.1016/j.cie.2017.02.009.

  • MA Muñoz, K. Smith-Miles. Generating custom classification datasets by targeting the instance space. GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1582-1588, 2017. doi: 10.1145/3067695.3082532.

  • Mehdi Foumani, K. Smith-Miles, Indra Gunawan. Scheduling of two-machine robotic rework cells: In-process, post-process and in-line inspection scenarios. Robotics and Autonomous Systems, 91, 210-225, 2017. doi: 10.1016/j.robot.2017.01.009.

  • Yanfei Kang, Rob J Hyndman, K. Smith-Miles. Visualising forecasting algorithm performance using time series instance spaces. International Journal of Forecasting, 33, 345-358, 2017. doi: 10.1016/j.ijforecast.2016.09.004.

  • Mehdi Foumani, Indra Gunawan, K. Smith-Miles. Increasing Throughput for a Class of Two-Machine Robotic Cells Served by a Multifunction Robot. IEEE Transactions on Automation Science and Engineering, 14, 1150-1159, 2017. doi: 10.1109/TASE.2015.2504478.

  • Ingrida Steponavice, Rob J Hyndman, K. Smith-Miles, Laura Villanova, I Steponavičė. Dynamic algorithm selection for pareto optimal set approximation. Journal of Global Optimization, 67, 263-282, 2017. doi: 10.1007/s10898-016-0420-x.

  • Mario A Munoz, K. Smith-Miles, MA Muñoz. Performance analysis of continuous black-box optimization algorithms via footprints in instance space. Evolutionary computation, 25, 529-554, 2017. doi: 10.1162/evco_a_00194.

  • Mario A Muñoz, K. Smith-Miles, M. Munoz Acosta. Non-parametric model of the space of continuous black-box optimization problems. Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '17, 2017. doi: 10.1145/3067695.3075971.

  • Shamsuddin N Ladha, K. Smith-Miles, Sharat Chandran. Realistic Projection on Casual Dual-Planar Surfaces with Global Illumination Compensation. International Journal of Image and Graphics, 16, 1650014 (29pp), 2016. doi: 10.1142/S0219467816500145.

  • Ingrida Steponavice, Mojdeh Shirazi-Manesh, Rob J Hyndman, K. Smith-Miles, Laura Villanova, I Steponavičė. On sampling methods for costly multi-objective black-box optimization. Springer Optimization and Its Applications, 107, 273-296, 2016. doi: 10.1007/978-3-319-29975-4_15.

  • Ingrida Steponavice, Mojdeh Shirazi-Manesh, Robin Hyndman, K. Smith-Miles, Laura Villanova. On Sampling Methods for Costly Multiobjective Black-box Optimization. 273-296, Springer International Publishing, 2016. doi: 10.1007/978-3-319-29975-4_15.

  • S. Ryan, S Kandanaarachchi, K. Smith-Miles. Support vector machines for characterising whipple shield performance. Procedia Engineering, 103, 522-529, 2015. doi: 10.1016/j.proeng.2015.04.068.

  • K. Smith-Miles. Incremental Learning. 731-735, Springer-Verlag New York Inc. Springer-Verlag New York Inc., 2015.

  • M. FOUMANI, K. Smith-Miles, I Gunawan, A. Moeini. Stochastic scheduling of an automated two-machine robotic cell with in-process inspection system. Proceedings - CIE 45: 2015 International Conference on Computers and Industrial Engineering, 2015.

  • M. FOUMANI, Indra Gunawan, K. Smith-Miles, M Yousef Ibrahim. Notes on feasibility and optimality conditions of small-scale multifunction robotic cell scheduling problems with pickup restrictions. IEEE Transactions on Industrial Informatics, 11, 821-829, 2015. doi: 10.1109/TII.2014.2371334.

  • M. FOUMANI, I Gunawan, K. Smith-Miles. Resolution of deadlocks in a robotic cell scheduling problem with post-process inspection system: Avoidance and recovery scenarios. IEEE International Conference on Industrial Engineering and Engineering Management, 2016-January, 1107-1111, 2015. doi: 10.1109/IEEM.2015.7385820.

  • Mario A Munoz, K. Smith-Miles. Effects of function translation and dimensionality reduction on landscape analysis. 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 1336-1342, 2015. doi: 10.1109/CEC.2015.7257043.

  • Yanfei Kang, Danijel Belusic, K. Smith-Miles, D BeluÅ¡ić. Classes of structures in the stable atmospheric boundary layer. Quarterly Journal of the Royal Meteorological Society, 141, 2057-2069, 2015. doi: 10.1002/qj.2501.

  • Pakize Taylan, Fatma Yerlikaya-Oezkurt, Gerhard-Wilhelm Weber, K. Smith-Miles. An approach to the mean shift outlier model by Tikhonov regularization and conic programming. INTELLIGENT DATA ANALYSIS, 18, 79-94, 2014. doi: 10.3233/IDA-130629.

  • Ingrida Steponavice, Robin Hyndman, K. Smith-Miles, Laura Villanova. Efficient identification of the Pareto optimal set. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8426 LNCS, 341-352, 2014. doi: 10.1007/978-3-319-09584-4_29.

  • Qianqian Wu, K. Smith-Miles, Tianhai Tian. Approximate Bayesian computation schemes for parameter inference of discrete stochastic models using simulated likelihood density.. BMC bioinformatics, 15, S3 (10pp), 2014. doi: 10.1186/1471-2105-15-S12-S3.

  • Yanfei Kang, Danijel Belusic, K. Smith-Miles, Danijel BeluÅ¡ić. A note on the relationship between turbulent coherent structures and phase correlation.. Chaos: An Interdisciplinary Journal of Nonlinear Science, 24, 023114 (6pp), 2014. doi: 10.1063/1.4875260.

  • K. Smith-Miles. Visualising the diversity of benchmark instances and generating new test instances to elicit insights into algorithm performance. PATAT 2014 - Proceedings of the 10th International Conference on the Practice and Theory of Automated Timetabling, 10, 2014.

  • K. Smith-Miles. Predicting Metaheuristic Performance on Graph Coloring Problems Using Data Mining. 417-432, Termedia Publishing HouseSpringer-Verlag Berlin HeidelbergSpringer-Verlag Berlin Heidelberg, 2013. doi: 10.1007/978-3-642-30671-6.

  • X. GENG, Chao Yin, Zhi-Hua Zhou, Xin Geng, K. Smith-Miles. Facial age estimation by learning from label distributions.. IEEE transactions on pattern analysis and machine intelligence, 35, 2401-2412, 2013. doi: 10.1109/TPAMI.2013.51.

  • Q Wu, K. Smith-Miles, T Tian. A two-variable model for stochastic modelling of chemical events with multi-step reactions. Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012, 270-275, 2012. doi: 10.1109/BIBM.2012.6392681.

  • K. Smith-Miles, Rafiq Islam. Meta-Learning of Instance Selection for Data Summarization. 77-95, Springer Science & Business Media, 2011. doi: 10.1007/978-3-642-20980-2_2.

  • Davide Carta, Laura Villanova, Stefano Costacurta, Alessandro Patelli, Irene Poli, Simone Vezzu, Paolo Scopece, Fabio Lisi, K. Smith-Miles, Rob J Hyndman, Anita J Hill, Paolo Falcaro, Simone Vezzù, Simone VezzuÌ€. Method for optimizing coating properties based on an evolutionary algorithm approach.. Analytical chemistry, 83, 6373-6380, 2011. doi: 10.1021/ac201337e.

  • K. Smith-Miles, Jano van Hemert. Discovering the suitability of optimisation algorithms by learning from evolved instances. Annals of Mathematics and Artificial Intelligence, 61, 87-104, 2011. doi: 10.1007/s10472-011-9230-5.

  • K. Smith-Miles. Exploratory Data Analysis. 486-488, Springer, 2010.

  • Joachim P Sturmberg, Eu-gene Siew, L. Churilov, K. Smith-Miles. Identifying patterns in primary care consultations:a cluster analysis. Journal of evaluation in clinical practice, 15, 558-564, 2009. doi: 10.1111/j.1365-2753.2009.01167.x.

  • Eu-Gene Siew, L. Churilov, K. Smith-Miles, Joachim P Sturmberg. Using supervised and unsupervised techniques to determine groups of patients with different doctor-patient stability. Advances in Knowledge Discovery and Data Mining, Proceedings, 5012, 715-+, 2008. doi: 10.1007/978-3-540-68125-0_68.

  • X. GENG, L Wang, M Li, Q Wu, K. Smith-Miles. Adaptive fusion of gait and face for human identification in video. Proceedings of the IEEE Workshop on Applications of Computer Vision, 1-6, 2008. doi: 10.1109/WACV.2008.4544006.

  • S Ali, K. Smith-Miles. On optimal degree selection for polynomial kernel with support vector machines: Theoretical and empirical investigations. International Journal of Knowledge-based and Intelligent Engineering Systems, 11, 1-18, 2007. doi: 10.3233/KES-2007-11101.

  • S Ali, KA Smith, K. Smith-Miles. Kernel width selection for SVM classification: A meta-learning approach. 101-115, IGI Global, 2007. doi: 10.4018/978-1-59904-528-3.ch006.

  • Mafruz Zaman Ashrafi, David Taniar, Kate Smith, K. Smith-Miles. Redundant association rules reduction techniques. International Journal of Business Intelligence and Data Mining, 2, 29-63, 2007. doi: 10.1504/IJBIDM.2007.012945.

  • LK Wickramasinghe, LD Alahakoon, K. Smith-Miles. A novel Episodic Associative Memory model for enhanced classification accuracy. Pattern Recognition Letters, 28, 1193-1202, 2007. doi: 10.1016/j.patrec.2007.02.012.

  • S Ali, KA Smith, K. Smith-Miles. Kernal Width Selection for SVM Classification: A Meta-Learning Approach. International Journal of Data Warehousing and Mining (IJDWM), 1, 78-97, 2005. doi: 10.4018/jdwm.2005100104.

  • M Ashrafi, D Taniar, K Smith, K. Smith-Miles. PPDAM: Privacy-Preserving Distributed Association-Rule-Mining Algorithm. International Journal of Intelligent Information Technologies (IJIIT), 1, 49-69, 2005. doi: 10.4018/jiit.2005010104.

  • E Siew, K. Smith-Miles, L. Churilov, J Wassertheil. A longitudinal comparison of supervised and unsupervised learning approaches to iso-resource grouping for acute healthcare in Australia. 283-303, Springer-Verlag Heidelberg, 2005. doi: 10.1007/11011620_18.

  • Ling Tan, David Taniar, Kate A Smith, K. Smith-Miles. A clustering algorithm based on an estimated distribution model. International Journal of Business Intelligence and Data Mining, 1, 229-245, 2005. doi: 10.1504/IJBIDM.2005.008364.

  • MZ Ashrafi, D Taniar, K Smith, K. Smith-Miles. ODAM: an optimized distributed association rule mining algorithm. IEEE Distributed Systems Online, 5, 1-18, 2004. doi: 10.1109/MDSO.2004.1285877.

  • J Black, G Benke, K Smith, L Fritsch, Lin Fritschi, K. Smith-Miles. Artificial neural networks and job-specific modules to assess occupational exposure.. The Annals of occupational hygiene, 48, 595-600, 2004. doi: 10.1093/glycob/meh064.

  • K. Smith-Miles. Artificial Neural Networks. Fonetik FilmsKluwer Academic Publishers, 2003. doi: 10.1007/b101874.

  • CCK Beh, PA Webley, KA Smith, K. Smith-Miles. The VSA process for oxygen enrichment: Process description and dynamic modeling using neural networks. International Journal of Smart Engineering System Design, 5, 1-9, 2003. doi: 10.1080/10255810305038.

  • S Ali, KA Smith, K. Smith-Miles. Matching SVM kernel's suitability to data characteristics using tree by fuzzy C-means clustering. DESIGN AND APPLICATION OF HYBRID INTELLIGENT SYSTEMS, 104, 553-562, 2003.

  • JM Garcia, S Lozano, K Smith, T Kwok, G Villa, K. Smith-Miles. Coordinated scheduling of production and delivery from multiple plants and with time windows using genetic algorithms. ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age, 3, 1153-1158, 2002. doi: 10.1109/ICONIP.2002.1202802.

  • T Kwok, K Smith, S Lozano, D Taniar, K. Smith-Miles. Parallel fuzzy c-means clustering for large data sets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2400, 365-374, 2002.

  • MZ Ashrafi, D Taniar, K Smith, K. Smith-Miles. A data mining architecture for distributed environments. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2346, 27-38, 2002.

  • S Lozano, JJ Domínguez, F Guerrero, K Smith, K. Smith-Miles. Genetic line search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2074, 318-326, 2001. doi: 10.1007/3-540-45718-6_36.

  • T Kwok, KA Smith, K. Smith-Miles. Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework.. Neural networks : the official journal of the International Neural Network Society, 13, 731-744, 2000. doi: 10.1016/S0893-6080(00)00047-2.

  • K Smith, M Krishnamoorthy, M Palaniswami, K. Smith-Miles. Neural versus traditional approaches to the location of interacting hub facilities. Recherche - Transports - Securite, 62, 155-171, 1999.

  • K Smith, M Palaniswami, M Krishnamoorthy, K. Smith-Miles. Neural techniques for combinatorial optimization with applications.. IEEE transactions on neural networks, 9, 1301-1318, 1998. doi: 10.1109/72.728380.

  • T Kwok, K Smith, LP Wang, K. Smith-Miles. Incorporating chaos into the Hopfield neural network for combinatorial optimisation. WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL 1, PROCEEDINGS, 659-665, 1998.

  • K Smith, M Palaniswami, K. Smith-Miles. Static and dynamic channel assignment using neural networks. IEEE Journal on Selected Areas in Communications, 15, 238-249, 1997. doi: 10.1109/49.552073.

  • K Smith, M Palaniswami, M Krishnamoorthy, K. Smith-Miles. A hybrid neural approach to combinatorial optimization. Computers and Operations Research, 23, 597-610, 1996. doi: 10.1016/0305-0548(95)00064-X.

  • K Smith, M Krishnamoorthy, M Palaniswami, K. Smith-Miles. Neural versus traditional approaches to the location of interacting hub facilities. Location Science, 4, 155-171, 1996. doi: 10.1016/S0966-8349(96)00017-4.

  • K Smith, M Palaniswami, M Krishnamoorthy, K. Smith-Miles. Traditional heuristic versus Hopfield neural network approaches to a car sequencing problem. European Journal of Operational Research, 93, 300-316, 1996. doi: 10.1016/0377-2217(96)00040-9.

  • K Smith, M Palaniswami, K. Smith-Miles. An improved Hopfield network approach to channel assignment in a cellular mobile communications network. Intelligent Engineering Systems Through Artificial Neural Networks, 6, 977-982, 1996.