DR Charl Ras

DR Charl Ras

Positions

  • Approximation algorithms
  • Combinatorial optimisation
  • Computational complexity
  • Network design
  • Operations research

Overview

OverviewText1

  • Charl Ras is a Lecturer in the School of Mathematics and Statistics at the University of Melbourne. His research primarily involves the use of techniques from graph theory, optimisation, and computational geometry for designing minimal networks. He is also interested in the design and asymptotic analysis of geometric network optimisation and approximation algorithms, including aspects such as computational complexity, fixed-parameter tractability, and approximability. Some of the applications of his work are the optimisation of energy consumption in wireless ad-hoc networks, VLSI design, and phylogenetic tree construction.

    One of Charl's current projects seeks to find tools and algorithms for the deployment and augmentation of optimal survivable networks. In this problem one is required to introduce a set of nodes and links into a geometric space so that the resultant network is multi-connected and is optimal with respect to some objective (for instance the sum of all link-lengths). Finding good solutions to this problem will contribute to the economical construction of robust infrastructure and telecommunications networks, including transportation networks, utility networks, and fibre-optic networks such as the NBN.   

Publications

Selected publications

Research

Awards

Education and training

  • PhD, University of Johannesburg 2008
  • Msc, University of Johannesburg 2003
  • BSc Hons, University of Johannesburg 2001
  • BSc, University of Johannesburg 2000

Supervision

Available for supervision

  • Y

Supervision Statement

  • I have a number of available projects in algorithms, network design and combinatorial optimisation. Some potential research topics include: Steiner trees, bounded-degree networks, survivable networks and the topological design of wireless sensor networks and other infrastructure networks. I would also be interested in supervising any projects at the intersection of combinatorial optimisation and approximation algorithms; including topics involving algorithm design, computational complexity and approximability.