School of Science, Engineering and Information Technology

Prof Adil Bagirov - Research

Graduate research supervisions

  • 25 PhD students have successfully completed
  • Currently: 3 PhD students

Current research projects/students

  • A.M. Bagirov, Large scale nonsmooth nonconvex optimisation: theory, numerical methods and applications, Australian Research Council Discovery Grant, DP190100580, $330K, 2019-2021.

Publications/conferences

Books

  1. Adil Bagirov, Napsu Karmitsa and Marko Makela, Introduction to Non-smooth Optimization: Theory, Practice and Software, Springer, 2014.
  2. A.Bagirov, N. Karmitsa and S. Taheri, Partitional Clustering via Nonsmooth Optimization. Springer, Cham, 2020.

Edited book

  1. A.Bagirov, M. Gaudioso, N. Karmitsa, M. Makela and S. Taheri (eds.), Numerical Nonsmooth Optimization. Springer, Cham, 2020.

Book chapters

  1. A.M. Bagirov, N. Sultanova, A. Al Nuaimat and S. Taheri, Solving minimax problems: Local smoothing versus global smoothing. In: M. Al-Baali, L. Grandinetti and A. Purnama (Eds), Numerical Analysis and Optimization, Springer, 23-43, 2018.
  2. A.M. Bagirov, S. Taheri, F. Bai and Z. Wu, An approximate ADMM for solving linearly constrained nonsmooth optimization problems with two blocks of variables. In: S. Hosseini, B.S. Mordukhovich and A. Uschmajew (Eds.), Nonsmooth Optimization and Its Applications, Birkhauser, Cham, International Series of Numerical Mathematics, Vol. 170, 17-44, 2019.
  3. K. Joki and A.M. Bagirov, Bundle methods for nonsmooth DC optimization. In: A. Bagirov, M. Gaudioso, N. Karmitsa, M. Makela and S. Taheri (Eds.), Numerical Nonsmooth Optimization, Springer, 263-296, 2020.
  4. A.M. Bagirov, N. Karmitsa and S. Taheri, Discrete gradient methods. In: A. Bagirov, M. Gaudioso, N. Karmitsa, M. Makela and S. Taheri (Eds.), Numerical Nonsmooth Optimization, Springer, 621-654, 2020.
  5. M. M. Makela, N. Karmitsa and A. Bagirov, Subgradient and bundle methods for non-smooth optimization, in: Numerical Methods for Differential Equations, Optimization, and Technological Problems, Special volume dedicated to P. Neittaanmaki, Springer, Netherlands, 2013, pp. 275-304.
  6. A.M. Bagirov, R. Kasimbeyli, G. Ozturk and J. Ugon, Piecewise linear classifiers based on nonsmooth optimization approaches, in: T.M. Rassias, C.A. Floudas, and S. Butenko (Eds.): Optimization in Science and Engineering, Springer, 2014, pp. 1-32.
  7. E. Mohebi and A.M. Bagirov, CR-Modified SOM to the Problem of Handwritten Digits Recognition, in: M. Bramer and M. Petridis Eds): Research and Development in Intelligent Systems XXXI, Springer, 2014, pp. 225-238.
  8. A.M. Bagirov and E. Mohebi, Non-smooth optimization based algorithms in cluster analysis, in: M.E. Celebi (ed): Partitional Clustering Algorithms, Springer, 2015, pp. 99-146.

Journal papers

  1. A.M. Bagirov , B. Karasozen, M. Sezer, Discrete gradient method: a derivative-free method for nonsmooth optimization. Journal of Optimization Theory and Applications, 137, 2008, 317-334.
  2. A.M. Bagirov , Modified global k-means algorithm for sum-of-squares clustering problems. Pattern Recognition, 41(10), 2008, 3192-3199.
  3. A.M. Bagirov , C.Clausen, M. Kohler, Estimation of a regression function by maxima of minima of linear functions. IEEE Transactions on Information Theory, 55(2), 2009, 833-845.
  4. A.M. Bagirov , C. Clausen, M. Kohler, An algorithm for the estimation of a regression function by continuous piecewise linear functions. Computational Optimization and Applications, 45(1), 2010, 159-179.
  5. A.M. Bagirov , A.N. Ganjehlou, A quasisecant method for minimizing nonsmooth functions. Optimization Methods and Software, 25(1), 2010, 3-18.
  6. A. Bagirov, C. Clausen, M. Kohler, An L2-boosting for estimation of a regression function. IEEE Transactions on Information Theory, 56(3), 2010, 1417-1429.
  7. A.M. Bagirov , A.N. Ganjehlou, J. Ugon, A.H. Tor, Truncated codifferential method for nonsmooth convex optimization. Pacific Journal of Optimization, 6(3), 2010, 483-496.
  8. A.M. Bagirov , J. Ugon, D. Webb, Fast modified global k-means algorithm for incremental cluster construction. Pattern Recognition, 44, 2011, 866-876.
  9. A.M. Bagirov , J. Ugon, D. Webb, An efficient algorithm for the incremental construction of a piecewise linear classifier. Information Systems, 36(4), 2011, 782-790.
  10. A.M. Bagirov , J. Ugon, D. Webb, B. Karasozen, Classification through incremental max-min separability. Pattern Analysis & Applications, 14(2), 2011, 165-174.
  11. A.M. Bagirov , J. Ugon, Codifferential method for minimizing nonsmooth DC functions. Journal of Global Optimization, 50(1), 2011, 3-22. N. Karmitsa, A. Bagirov, M. Makela, Comparing different nonsmooth minimization methods and software. Optimization Methods and Software, 27(1), 2012, 131-153.
  12. N. Karmitsa, A.M. Bagirov , Limited memory discrete gradient bundle method for nonsmooth derivative free optimization. Optimization, 61 (12), 2012, 1491-1509.
  13. A.M. Bagirov , A. Al Nuaimat, N. Sultanova, Hyperbolic smoothing function method for minimax problems. Optimization, 62 (6), 2013, 759-782.
  14. A.M. Bagirov , J. Ugon, D.Webb, G. Ozturk, R. Kasimbeyli, A novel piecewise linear classifier based on polyhedral conic and max-min separabilities. TOP: Journal of Spanish Operational Research Society, 21(1), 2013, 3-24.
  15. A.M. Bagirov , L. Jin, N. Karmitsa, A. Al Nuaimat, N. Sultanova, Subgradient method for nonconvex nonsmooth optimization. Journal of Optimization Theory and Applications, 157(2), 2013, 416-435.
  16. A.M. Bagirov , A.F. Barton, H. Mala-Jetmarova, A. Al Nuaimat, S.T. Ahmed, N. Sultanova, J. Yearwood, An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling. Mathematical and Computer Modelling, 57(3), 2013, 873-886.
  17. A.M. Bagirov , J. Ugon, H. Mirzayeva, Nonsmooth nonconvex optimization approach to clusterwise linear regression problems. European Journal of Operational Research, 229(1), 2013, 132-142.
  18. A.H. Tor, A. Bagirov, B. Karasozen, Aggregate codifferential method for nonsmooth DC optimization. Journal of Computational and Applied Mathematics, 259, 2014, 851-867.
  19. E. Mohebi, A. Bagirov, A convolutional recursive modified self-organizing map for Handwritten digits recognition learning systems. Neural Networks, 60, 2014, 104-118.
  20. A. Ferrer, A. Bagirov, G. Beliakov, Solving DC programs using the cutting angle method. Journal of Global Optimization, 61(1), 2015, 71-89.
  21. B. Ordin, A.M. Bagirov , A heuristic algorithm for solving the minimum sum-of squares clustering problems. Journal of Global Optimization, 61(2), 2015, 341-361.
  22. A.M. Bagirov , J. Ugon, H.G. Mirzayeva, Nonsmooth optimization algorithm for solving clusterwise linear regression problems. Journal of Optimization Theory and Applications, 164(3), 2015, 755-780.
  23. A.M. Bagirov , J. Ugon, H.G. Mirzayeva, An algorithm for clusterwise linear regression based on smoothing techniques. Optimization Letters, 9(2), 2015, 375-390.
  24. E. Mohebi, A. Bagirov, Modified self-organizing maps with a new topology and initialization algorithm. Journal of Experimental & Theoretical Artificial Intelligence, 27(3), 2015, 351-372.
  25. H. Mala-Jetmarova, A. Barton, A. Bagirov, History of water distribution systems and their optimisation. Water Science & Technology: Water Supply, 15(2), 2015, 224-235.
  26. H. Mala-Jetmarova, A. Barton, A. Bagirov, Exploration of the trade-offs between water quality and pumping costs in optimal operation of regional multiquality water distribution systems. Journal of Water Resources Planning and Management, 141(6), 2015, 04014077.
  27. A.M. Bagirov , B. Ordin, G. Ozturk, A.E. Xavier, An incremental clustering algorithm based on hyperbolic smoothing. Computational Optimization and Applications, 61, 2015, 219-241.
  28. G. Ozturk, A.M. Bagirov , R. Kasimbeyli, An incremental piecewise linear classifier based on polyhedral conic separation. Machine Learning, 101 (1-3), 2015, 397-413.
  29. H. Mala-Jetmarova, A. Barton, A. Bagirov, Impact of water quality conditions in source reservoirs on the optimal operation of a regional multiquality water distribution system. Journal of Water Resources Planning and Management, 141 (10), 2015, 04015013.
  30. H. Mala-Jetmarova, A. Barton, A. Bagirov, Sensitivity of algorithm parameters and objective function scaling in multi-objective optimisation of water distribution systems. Journal of Hydroinformatics, 17 (6), 2015, 891-916.
  31. A.M. Bagirov , S. Taheri, J. Ugon, Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems. Pattern Recognition, 53, 2016, 12-24.
  32. A.M. Bagirov , E. Mohebi, An algorithm for clustering using L1-norm based on hyperbolic smoothing technique. Computational Intelligence, 32(3), 2016, 439-457.
  33. E. Mohebi, A. Bagirov, Constrained self-organizing maps for data clusters visualization. Neural Processing Letters, 43(3), 2016, 849-869.
  34. A.M. Bagirov , A. Mahmood, A. Barton, Prediction of monthly rainfall in Victoria, Australia: Clusterwise linear regression approach. Atmospheric Research, 188, 2017, 20-29.
  35. K. Joki, A. Bagirov, N. Karmitsa, M. Makela, A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes. Journal of Global Optimization, 68(3), 2017, 501-535.
  36. A.M. Bagirov , S. Taheri, DC programming algorithm for clusterwise linear L1 regression. Journal of Operations Research Society of China, 5(2), 2017, 233-256.
  37. S. Seifollahi, A. Bagirov, R. Layton, I. Gondal, Optimization based clustering algorithms for authorship analysis of phishing emails. Neural Processing Letters, 46(2), 2017, 411-425.
  38. N. Karmitsa, A.M. Bagirov , S. Taheri, New diagonal bundle method for clustering problems in large data sets. European Journal of Operational Research, 263(2), 2017, 367-379.
  39. A.M. Bagirov , J. Ugon, Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms. Optimization Methods and Software, 33 (1), 2018, 194-219.
  40. M. Gaudioso, G. Giallombardo, G. Miglionico, A.M. Bagirov , Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations. Journal of Global Optimization, 71(1), 2018, 37-55.
  41. K. Joki, A.M. Bagirov , N. Karmitsa, M.M. Makela, S. Taheri, Double bundle method for finding Clarke stationary points in nonsmooth DC programming, SIAM Journal on Optimization, 28 (2), 2018, 1892-1919.
  42. A.M. Bagirov , A. Mahmood, A comparative assessment of models to predict monthly rainfall in Australia. Water Resources Management, 32 (5), 2018, 1777-1794.
  43. N. Karmitsa, A.M. Bagirov , S. Taheri, Clustering in large data sets with the limited memory bundle method. Pattern Recognition, 83, 2019, 245-259.
  44. A. Bagirov, S. Taheri, S. Asadi, A difference of convex optimization algorithm for piecewise linear regression. Journal of Industrial and Management Optimization, 15(2), 2019, 909-932.
  45. A.M. Bagirov , G. Ozturk, R. Kasimbeyli, A sharp augmented Lagrangian-based method in constrained non-convex optimization. Optimization Methods and Software, 34(3), 2019, 462-488.
  46. S. Seifollahi, A. Bagirov, E.Z. Borzeshi, M. Piccardi, A simulated annealing-based maximum margin clustering algorithm. Computational Intelligence, 35(1), 2019, 23-41.
  47. I. Grigoryev, A. Bagirov, M. Tuck, Prediction of gold-bearing localised occurrences from limited exploration data. International Journal of Computational Science and Engineering 21 (4), 503-512, 2020.
  48. A.M. Bagirov, A. Al Nuaimat, N. Sultanova, Hyperbolic smoothing function method for minimax problems, Optimization, 62 (6), 2013, 759-782.
  49. A. Stranieri, A. Yatsko, I. Golden, M. Mammadov, A. Bagirov, Capped k-NN editing in definition lacking environments, Journal of Pattern Recognition Research, 1, 2013, 39-58.
  50. A.M. Bagirov, A.M, J. Ugon, D. Webb, G. Ozturk and R. Kasimbeyli, A novel piecewise linear classifier based on polyhedral conic and max-min separability, TOP: Journal of Spanish Operational Research Society, 21(1), 2013, 3-24.
  51. A.M. Bagirov, L. Jin, N. Karmitsa, A. Al Nuaimat, N. Sultanova, Sub-gradient method for non-convex non-smooth optimization, Journal of Optimization Theory and Applications, 157(2), 2013, 416-435.
  52. A.M. Bagirov, A.F. Barton, H. Mala-Jetmarova, A. Al Nuaimat, S.T. Ahmed, N. Sultanova, J. Yearwood, An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling, Mathematical and Computer Modelling, 57(3), 2013, 873-886.
  53. A.M. Bagirov, J. Ugon, H. Mirzayeva, Nonsmooth nonconvex optimization approach to clusterwise linear regression problems, European Journal of Operational Research, 229(1), 2013, 132-142.
  54. A.H. Tor, A. Bagirov, B. Karasozen, Aggregate codifferential method for nonsmooth DC optimization, Journal of Computational and Applied Mathematics, 259, 2014, 851-867.
  55. E. Mohebi and A. Bagirov, A convolutional recursive modified self organizing map for Handwritten digits recognition learning systems, Neural Networks, 60, 2014, 104-118.
  56. A. Ferrer, A. Bagirov, G. Beliakov, Solving DC programs using the cutting angle method, Journal of Global Optimization, 61(1), 2015, 71-89.
  57. B. Ordin, A.M. Bagirov, A heuristic algorithm for solving the minimum sum-of-squares clustering problems, Journal of Global Optimization, 61(2), 2015, 341-361.
  58. A.M. Bagirov, J. Ugon, H.G. Mirzayeva, Nonsmooth optimization algorithm for solving cluster-wise linear regression problems, Journal of Optimization Theory and Applications, 164(3), 2015, 755-780.
  59. A.M. Bagirov, J. Ugon, H.G. Mirzayeva, An algorithm for cluster-wise linear regression based on smoothing techniques, Optimization Letters, 9(2), 2015, 375-390.
  60. E. Mohebi and A. Bagirov, Modified self organizing maps with a new topology and initialization algorithm, Journal of Experimental & Theoretical Artificial Intelligence, 27(3), 2015, 351-372.
  61. H. Mala-Jetmarova, A. Barton, A. Bagirov, History of water distribution systems and their optimisation, Water Science & Technology: Water Supply, 15(2), 2015, 224-235.
  62. H. Mala-Jetmarova, A. Barton and A. Bagirov, Exploration of the trade-offs between water quality and pumping costs in optimal operation of regional multiquality water distribution systems. Journal Water Resources Planning and Management, 141(6), 2015, 04014077.
  63. H. Mala-Jetmarova, A. Barton, A. Bagirov, Erratum for "Exploration of the Trade-Offs between Water Quality and Pumping Costs in Optimal Operation of Regional Multiquality Water Distribution Systems", Journal Water Resources Planning and Management, 141(2), 2015.
  64. A.M. Bagirov, B. Ordin, G. Ozturk and A.E. Xavier, An incremental clustering algorithm based on hyperbolic smoothing, Computational Optimization and Applications, 61, 2015, 219-241.
  65. H.F. Jelinek, A. Yatsko, A. Stranieri, S. Venkatraman and A. Bagirov, Diagnostic with incomplete nominal/discrete data, Artificial Intelligence Research, 2015, p 22.
  66. H. Mala-Jetmarova, A. Barton, A. Bagirov, Impact of water quality conditions in source reservoirs on the optimal operation of a regional multiquality water distribution system, Journal of Water Resources Planning and Management, accepted for publication on January 8, 2015.
  67. G. Ozturk, A.M. Bagirov and R. Kasimbeyli, An incremental piece-wise linear classifier based on polyhedral conic separation, Machine Learning, accepted for publication. DOI: 10.1007/s10994-014-5449-9.
  68. A.M. Bagirov and E. Mohebi, An algorithm for clustering using L1-norm based on hyperbolic smoothing technique, Computational Intelligence, accepted for publication.
  69. H. Mala-Jetmarova, A. Barton, A. Bagirov, Sensitivity of algorithm parameters and objective function scaling in multi-objective optimisation of water distribution systems, Journal of Hydroinformatics, accepted for publication.
  70. E. Mohebi and A. Bagirov, Constrained self organizing maps for data clusters visualization, Neural Processing Letters, accepted for publication.

Refereed conference papers

  1. H. Mala-Jetmarova, A. Bagirov and A. Barton. Pumping Costs and Water Quality in the Battlefield of Optimal Operation of Water Distribution Networks. 35th IAHR World Congress (IAHR 2013), Chengdu, China, 8-13 September 2013.
  2. A.M. Bagirov and E. Mohebi, A New Modification of Kohonen Neural Network for VQ and Clustering Problems, Proceedings of the Eleventh Australasian Data Mining Conference (AusDM 2013), Canberra, 13-15 November 2013. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 146.
  3. H. Mala-Jetmarova, A. Barton and A. Bagirov, Optimal Operation of a Multiquality Water Distribution System with Changing Turbidity and Salinity Levels in Source Reservoirs. 16th Water Distribution Systems Analysis Conference (WDSA 2014), Bari, Italy, 14-17 July 2014, Procedia Engineering, Elsevier, 89, 2014, 197-205.

Professional memberships and associations

  • Australian Mathematical Society
  • ANZIAM

Research interests

  • Optimisation
  • Non-smooth analysis
  • Non-smooth optimisation
  • Global optimisation
  • Operations research
  • Data mining
  • Optimisation of water distribution systems
  • Computational intelligence

Editorial memberships

  • Journal of Global Optimization
  • Optimization
  • Pacific Journal of Optimization
  • Journal of Industrial and Management Optimization
  • International Journal of Mathematical Modelling and Numerical Optimization
  • Journal of Optimization (Hindawi)

Potential honours and PhD projects

  • Large scale problems in nonsmooth optimisation
  • Large scale problems in global optimisation
  • Optimisation approaches in Machine Learning.