Qualifications

PhD, Curtin University, 2013

Graduate Certificate of Education (Tertiary Teaching), 2016

Work Experience

1. Virgina Tech

2. Federation University

3. Monash University

Research Areas

1. Electric vehicles operations

    Ruan, N, Andrew, L. H. and Vu, H. L., Optimization of shared autonomous electric vehicles operations, submitted, 2023.

2. Sensor network

    Ruan, N. and Gao, D.Y. (2014), Global optimal solutions to general sensor network localization problem. Performance Evaluation. 75-76, 1-16.

    Gao, D.Y., Ruan, N. and Pardalos, P.M. (2012), Canonical dual solutions to sum of fourth-order polynomials minimization problems with applications to sensor network localization, in Sensors: Theory, Algorithms, and Applications. Springer, 61, 37-54.

3. Machine learning

   Ruan, N., Chen, Y. and Gao, D.Y. (2013), An efficient classification using support vector machines. Proceedings of 2013 Science and Information conference, The Science and Information Organization, 585-589.

4. Dynamical systems

   Ruan, N., and Gao, D. Y. (2014), Canonical duality approach for nonlinear dynamical  systems. IMA Journal of Applied Mathematics, 79(2), 313-325.

5. Reliability systems

  Ruan, N. and Sun, X. L. (2006). An exact algorithm for cost minimization in series reliability systems with multiple component choices. Applied Mathematics and Computation, 181(1), 732-741.

  Sun, X. L., Ruan, N. and Li, D. (2006). An efficient algorithm for nonlinear integer programming problems arising in series-parallel reliability systems. Optimization Methods and Software, 21(4), 617-633.

6. Math programming

   1) Fix point problem

   Ruan, N. and Gao, D. Y. (2018),  On modeling and complete solutions to general fixpoint problems in multi-scale systems with applications. Fixed Point Theory and Applications. 2018:23.

   2) Fractional programming

   Ruan, N. and Gao, D.Y. (2015), Global solutions to fractional programming problem with ratio of nonconvex functions. Applied Mathematics and Computation. 255, 66-72.

   3) Mixed integer programming

  Ruan, N., and Gao, D. Y. (2017), Global optimal solution to quadratic discrete programming problem with inequality constraints, in Canonical Duality Theory: Unified Methodology for Multidisciplinary Study, Springer, 37, 315-338.

   Gao, D.Y., Ruan, N. and Sherali, H. D. (2010), Canonical dual solutions to fixed cost quadratic programs, in Optimization and Optimal Control: Theory and Applications. Springer, 39, 139-156.

  Gao, D.Y. and Ruan, N. (2010), Solutions to quadratic minimization problems with box and integer constraints, Journal of Global Optimization, 47(3), 463-484.

   4) Nonconvex optimization

   Ruan, N. and Gao, D.Y. (2017), Canonical duality theory for solving nonconvex/discrete constrained global optimization problems, in Canonical Duality Theory: Unified Methodology for Multidisciplinary Study, Springer, 37, 187-201.

  Gao, D.Y. , Ruan, N. and Latorre, V. (2017), Canonical duality-triality: Bridge between nonconvex analysis/mechanics and global optimization in complex system, in Canonical Duality Theory: Unified Methodology for Multidisciplinary Study, Springer, 37, 1-47.

  Ruan, N., Gao, D.Y., and Jiao, Y. (2010), Canonical dual least square method for solving general nonlinear systems of quadratic equations, Computational Optimization and Applications, 47(2), 335-347.

  Gao, D.Y., Ruan, N. and Sherali, H. D. (2009), Solutions and optimality criteria for  nonconvex constrained global optimization problems with connections between canonical and Lagrangian duality, Journal of Global Optimization, 45(3), 473-497.

  Gao, D.Y. and Ruan, N. (2008), Complete solutions and optimality criteria for nonconvex quadratic-exponential minimization problem, Mathematical Methods of Operations Research, 67(3), 479-491.

Edited book

  Gao, D.Y., Latorre, V. and Ruan, N. (2017), Canonical Duality Theory: Unified Methodology for Multidisciplinary Study, Springer, New York, 37, 377pp.

  Gao, D.Y., Ruan, N. and Xing, W. X. (2015), Advances in Global Optimization, Springer, New York. 95, 537pp.

Research grant

 US Air Force AFOSR : Canonical Duality Theory and Algorithm for Solving ‘NP-Hard Problems’ in Decision Science and Complex Systems, $450K, 2017-2020, with Gao, D.Y.

Computational Expertise

  Python, MATLAB, Fortran, Mathematica

Membership

  IEEE, senior member

Contact: ning.ruan.research@gmail.com