Dr Ali Ahrari

Lecturer

Doctor of Philosophy in Mechanical Engineering (December 2016), Michigan State University, East Lansing, MI, USA (GPA: 4.00/4)
Master of Science in Mechanical Engineering-Applied Design (September 2009), University of Tehran, Tehran, Iran
Bachelor of Science in Mechanical Engineering-Solid Mechanics (September 2006), University of Tehran, Tehran, Iran

UNSW Canberra
School of Systems & Computing

Ali Ahrari received his Bachelor's and Master's degrees in mechanical engineering from the University of Tehran in 2006 and 2009, respectively. He received his Ph.D. in mechanical engineering from Michigan State University (MSU) in 2016 and subsequently worked as a research associate at MSU until June 2018. He has won some international competitions on optimization such as "Competition on niching methods for multimodal optimization" in 2016 and 2020, which was held at CEC and GECCO conferences, as well as international student competition on structural optimization (ISCSO) in 2017 and 2018 and received a 1000 euro cash prizes. Since July 2018, he is working at UNSW-Canberra as a research associate in the Canberra Evolutionary Optimization group. His current research concentrates on evolutionary dynamic and noisy optimization with a focus on multimodal and multiobjective problems. 

Location
Building 15, Room 104
  • Book Chapters | 2022
    Ahrari A; Essam D, 2022, 'An Introduction to Evolutionary and Memetic Algorithms for Parameter Optimization', in Adaptation, Learning, and Optimization, pp. 37 - 63, http://dx.doi.org/10.1007/978-3-030-88315-7_3
    Book Chapters | 2021
    Ahrari A; Deb K, 2021, 'Multimodal Optimization by Evolution Strategies with Repelling Subpopulations', in Metaheuristics for Finding Multiple Solutions, pp. 145 - 163, http://dx.doi.org/10.1007/978-3-030-79553-5_7
  • Journal articles | 2023
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello Coello CA, 2023, 'Revisiting Implicit and Explicit Averaging for Noisy Optimization', IEEE Transactions on Evolutionary Computation, 27, pp. 1250 - 1259, http://dx.doi.org/10.1109/TEVC.2022.3201090
    Journal articles | 2023
    Ahrari A; Verstraete D, 2023, 'Online model tuning in surrogate-assisted optimization — An effective approach considering the cost–benefit tradeoff', Swarm and Evolutionary Computation, 82, pp. 101357 - 101357, http://dx.doi.org/10.1016/j.swevo.2023.101357
    Journal articles | 2022
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello CAC, 2022, 'PyDDRBG: A Python framework for benchmarking and evaluating static and dynamic multimodal optimization methods', SoftwareX, 17, http://dx.doi.org/10.1016/j.softx.2021.100961
    Journal articles | 2022
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello CAC, 2022, 'Static and Dynamic Multimodal Optimization by Improved Covariance Matrix Self-Adaptation Evolution Strategy with Repelling Subpopulations', IEEE Transactions on Evolutionary Computation, 26, pp. 527 - 541, http://dx.doi.org/10.1109/TEVC.2021.3117116
    Journal articles | 2021
    Ahrari A; Blank J; Deb K; Li X, 2021, 'A proximity-based surrogate-assisted method for simulation-based design optimization of a cylinder head water jacket', Engineering Optimization, 53, pp. 1574 - 1592, http://dx.doi.org/10.1080/0305215X.2020.1808972
    Journal articles | 2021
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello CAC, 2021, 'A Novel Parametric benchmark generator for dynamic multimodal optimization', Swarm and Evolutionary Computation, 65, http://dx.doi.org/10.1016/j.swevo.2021.100924
    Journal articles | 2021
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello CAC, 2021, 'A heredity-based adaptive variation operator for reinitialization in dynamic multi-objective problems', Applied Soft Computing, 101, pp. 107027, http://dx.doi.org/10.1016/j.asoc.2020.107027
    Journal articles | 2021
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello Coello CA, 2021, 'Adaptive Multilevel Prediction Method for Dynamic Multimodal Optimization', IEEE Transactions on Evolutionary Computation, 25, pp. 463 - 477, http://dx.doi.org/10.1109/TEVC.2021.3051172
    Journal articles | 2021
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello Coello CA, 2021, 'Weighted pointwise prediction method for dynamic multiobjective optimization', Information Sciences, 546, pp. 349 - 367, http://dx.doi.org/10.1016/j.ins.2020.08.015
    Journal articles | 2021
    Mahmud F; Zaman F; Ahrari A; Sarker R; Essam D, 2021, 'Genetic Algorithm for Singular Resource Constrained Project Scheduling Problems', IEEE Access, 9, pp. 131767 - 131779, http://dx.doi.org/10.1109/ACCESS.2021.3114702
    Journal articles | 2020
    Ahrari A; Atai AA; Deb K, 2020, 'A customized bilevel optimization approach for solving large-scale truss design problems', Engineering Optimization, 52, pp. 2062 - 2079, http://dx.doi.org/10.1080/0305215X.2020.1740690
    Journal articles | 2018
    Ahrari A; Deb K, 2018, 'A Novel Class of Test Problems for Performance Evaluation of Niching Methods', IEEE Transactions on Evolutionary Computation, 22, pp. 909 - 919, http://dx.doi.org/10.1109/TEVC.2017.2775211
    Journal articles | 2017
    Ahrari A; Deb K; Preuss M, 2017, 'Multimodal optimization by covariance matrix self-adaptation evolution strategy with repelling subpopulations', Evolutionary Computation, 25, pp. 439 - 471, http://dx.doi.org/10.1162/EVCO_a_00182
    Journal articles | 2017
    Ahrari A; Kramer O, 2017, 'Finite life span for improving the selection scheme in evolution strategies', Soft Computing, 21, pp. 501 - 513, http://dx.doi.org/10.1007/s00500-015-1805-3
    Journal articles | 2017
    Ahrari A; Lei H; Sharif MA; Deb K; Tan X, 2017, 'Design optimization of an artificial lateral line system incorporating flow and sensor uncertainties', Engineering Optimization, 49, pp. 328 - 344, http://dx.doi.org/10.1080/0305215X.2016.1168108
    Journal articles | 2017
    Ahrari A; Lei H; Sharif MA; Deb K; Tan X, 2017, 'Reliable underwater dipole source characterization in 3D space by an optimally designed artificial lateral line system', Bioinspiration and Biomimetics, 12, http://dx.doi.org/10.1088/1748-3190/aa69a4
    Journal articles | 2016
    Ahrari A; Deb K, 2016, 'An improved fully stressed design evolution strategy for layout optimization of truss structures', Computers and Structures, 164, pp. 127 - 144, http://dx.doi.org/10.1016/j.compstruc.2015.11.009
    Journal articles | 2015
    Ahrari A; Atai AA; Deb K, 2015, 'Simultaneous topology, shape and size optimization of truss structures by fully stressed design based on evolution strategy', Engineering Optimization, 47, pp. 1063 - 1084, http://dx.doi.org/10.1080/0305215X.2014.947972
    Journal articles | 2015
    Ahrari A; Shariat-Panahi M, 2015, 'An improved evolution strategy with adaptive population size', Optimization, 64, pp. 2567 - 2586, http://dx.doi.org/10.1080/02331934.2013.836651
    Journal articles | 2013
    Ahrari A; Atai AA, 2013, 'EFFICIENT SIMULATION FOR OPTIMIZATION OF TOPOLOGY, SHAPE AND SIZE OF MODULAR TRUSS STRUCTURES', International Journal of Optimization in Civil Engineering, 3, pp. 209-223 - 223, http://ijoce.iust.ac.ir/article-1-128-en.html
    Journal articles | 2013
    Ahrari A; Atai AA, 2013, 'Fully stressed design evolution strategy for shape and size optimization of truss structures', Computers and Structures, 123, pp. 58 - 67, http://dx.doi.org/10.1016/j.compstruc.2013.04.013
    Journal articles | 2013
    Ahrari A, 2013, 'A requirement for the mutation operator in continuous optimization', Optimization Letters, 7, pp. 1681 - 1690, http://dx.doi.org/10.1007/s11590-012-0514-4
    Journal articles | 2012
    Ahrari F; Ramazanzadeh BA; Sabzevari B; Ahrari A, 2012, 'The effect of fluoride exposure on the load-deflection properties of superelastic nickel-titanium-based orthodontic archwires.', Australian orthodontic journal, 28, pp. 72 - 79
    Journal articles | 2011
    Ramazanzadeh BA; Ahrari F; Sabzevari B; Zebarjad SM; Ahrari A, 2011, 'Effects of a simulated oral environment and sterilization on load-deflection properties of superelastic nickel titanium-based orthodontic wires.', International journal of orthodontics (Milwaukee, Wis.), 22, pp. 13 - 21
    Journal articles | 2010
    Ahrari A; Ahrari R, 2010, 'On the utility of randomly generated functions for performance evaluation of evolutionary algorithms', Optimization Letters, 4, pp. 531 - 541, http://dx.doi.org/10.1007/s11590-010-0181-2
    Journal articles | 2010
    Ahrari A; Atai AA, 2010, 'Grenade Explosion Method - A novel tool for optimization of multimodal functions', Applied Soft Computing Journal, 10, pp. 1132 - 1140, http://dx.doi.org/10.1016/j.asoc.2009.11.032
    Journal articles | 2010
    Ahrari A; Saadatmand MR; Shariat-Panahi M; Atai AA, 2010, 'On the limitations of classical benchmark functions for evaluating robustness of evolutionary algorithms', Applied Mathematics and Computation, 215, pp. 3222 - 3229, http://dx.doi.org/10.1016/j.amc.2009.10.009
    Journal articles | 2009
    Ahrari A; Shariat-Panahi M; Atai AA, 2009, 'GEM: A novel evolutionary optimization method with improved neighborhood search', Applied Mathematics and Computation, 210, pp. 376 - 386, http://dx.doi.org/10.1016/j.amc.2009.01.009
  • Conference Papers | 2021
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello Coello CA, 2021, 'Modular Analysis and Development of a Genetic Algorithm with Standardized Representation for Resource-Constrained Project Scheduling', in 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings, IEEE, ELECTR NETWORK, pp. 612 - 619, presented at IEEE Congress on Evolutionary Computation (IEEE CEC), ELECTR NETWORK, 28 June 2021 - 01 July 2021, http://dx.doi.org/10.1109/CEC45853.2021.9504950
    Conference Papers | 2020
    Ahrari A; Elsayed S; Sarker R; Essam D; Coello CAC, 2020, 'Towards a More Practically Sound Formulation of Dynamic Problems and Performance Evaluation of Dynamic Search Methods', in 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, pp. 1387 - 1394, http://dx.doi.org/10.1109/SSCI47803.2020.9308464
    Conference Papers | 2019
    Ahrari A; Elsayed S; Sarker R; Essam D, 2019, 'A New Prediction Approach for Dynamic Multiobjective Optimization', in 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, IEEE Xplore, Wellington, New Zealand, New Zealand, pp. 2268 - 2275, presented at Congress on Evolutionary Computation (CEC), Wellington, New Zealand, New Zealand, 10 June 2019 - 13 June 2019, http://dx.doi.org/10.1109/CEC.2019.8790215
    Conference Papers | 2017
    Ahrari A; Deb K; Mohanty S; Hattel JH, 2017, 'Multi-objective optimization of cellular scanning strategy in selective laser melting', in 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings, pp. 2730 - 2737, http://dx.doi.org/10.1109/CEC.2017.7969639
    Conference Papers | 2016
    Ahrari A; Lei H; Sharif MA; Deb K; Tan X, 2016, 'Optimum design of artificial lateral line systems for object tracking under uncertain conditions', in GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference, pp. 123 - 124, http://dx.doi.org/10.1145/2908961.2909040
    Conference Papers | 2015
    Ahrari A; Lei H; Sharif MA; Deb K; Tan X, 2015, 'Design optimization of artificial lateral line system under uncertain conditions', in 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, pp. 1807 - 1814, http://dx.doi.org/10.1109/CEC.2015.7257106

$3718 from the UNSW high-performance computing (HPC) resource allocation scheme

2020            Winner of competition on niching methods for multimodal optimisation at IEEE WCCI/CEC'2020 (500 USD cash prize from IEEE) and GECCO'2020

2018            Winner of 2018 ISCSO competition on structural optimisation (1000 € prize)

2017            Winner of GECCO'2017 competition on multi-modal optimisation

2017             Winner of the 2017 ISCSO competition on structural optimisation among 60+ participants (1000 € prize)

2016             Winner of GECCO'2016, CEC'2016 competitions on multimodal optimisation

2016             Passed the FE/EIT mechanical engineering exam in the state of Michigan, USA

2013-2016   Graduate Office Fellowship (This fellowship was awarded multiple times)

2012             Richard H. Brown – ME Endowment Award

       

I carry out research on developing optimization algorithms, both classical methods and evolutionary algorithms, and their specialization for engineering problems. Engineering Design by optimization is my favorite subject. I have also some experience in machine learning, specifically Decision trees and neural networks.  Currently, I am doing research on “Reactive planning under disruptions and dynamic changes”, which is funded by the Australian Research Council. In the past, I have worked on evolutionary optimization-related projects funded by General Motors Company, Ford Motor Company, REWIND, NSF, and a few other projects that were not funded.

We may have a funded position for a graduate student (PhD or Master’s by research). If you have a background, expertise, and interest in design optimisation, evolutionary algorithms, or even machine learning, feel free to email me with the following information:

  1. CV +  publication list
  2. Transcripts
  3. English test score. You can find about the scores here: https://www.unsw.edu.au/english-requirements-policy
  4. Your research proposal (1-2 pages).  Depending on your research interest, it is suggested that you visit  EvOpt group website (https://sites.google.com/view/evopt/home) or MDO lab (http://www.mdolab.net/).

 

 

My Research Supervision

1 PhD student at SEIT, UNSW-Canberra