Dr. Mustafa Rizvi
Lecturer, Applied Mathematics and Statistics
Dr. Mohammed Mustafa Rizvi is a Lecturer in Applied Mathematics and Statistics at Federation University Australia. His expertise spans a range of exciting areas, including optimisation, multiobjective optimisation, mathematical modelling, optimal control and operations research. Mustafa's research journey involves implementing numerical techniques and designing algorithms to tackle large-scale optimisation problems.
Beyond research, Dr. Mustafa bridges academia and industry by leading impactful research projects in collaboration with industry partners like the Defence Science and Technology Group, Australia. In recognition of outstanding contributions, he and his team received the DST Certificate of Recognition Award in 2019.
Dr. Mustafa published his novel research papers in high-ranking journals, including the Journal of Optimization Theory and Applications, SIAM Journal on Optimization, and Engineering Optimization. He supervised two PhD students in optimisation and optimal control. He completed his Ph.D. in multiobjective optimisation from the University of South Australia and holds an MPhil from the University of Chittagong, Bangladesh.
Algorithms for generating Pareto fronts of multi-objective integer and mixed-integer programming problems
Multiobjective reverse logistics model for inventory management with environmental impacts: An application in industry
Optimal path planning of Unmanned Aerial Vehicles (UAVs) for targets touring: Geometric and arc parameterization approaches
A new scalarization technique and new algorithms to generate pareto fronts
A New Scalarization Technique to Approximate Pareto Fronts of Problems with Disconnected Feasible Sets
Proper Efficiency and Proper Karush–Kuhn–Tucker Conditions for Smooth Multiobjective Optimization Problems
On Weak and Strong Kuhn-Tucker Conditions for Smooth Multiobjective Optimization
New second-order optimality conditions in multiobjective optimization problems: Differentiable case