Time: 1:00pm Tuesday 26, 2013
Location: SIT 123 Lecture Theatre
Speaker: Frank Neumann, University of Adelaide
General purpose algorithms are often applied when no good problem specific algorithm is available. Many of such algorithms are inspired by optimization processes in nature and fall into the area of bio-inspired computing. Bio-inspired computing includes well-known approaches such as evolutionary algorithms and ant colony optimization.
The theoretical understanding of these, in practice successful, algorithms has gained increasing interest in recent years. Studying the computational complexity of bio-inspired computing has become a major part in their theoretical analysis.
We investigate bio-inspired computing methods in the context of parameterized complexity and present results for this new research area by considering two classical problems, namely the vertex cover problem and the Euclidean traveling salesperson problem.
Joint work with Stefan Kratsch and Andrew Sutton