This course gives an overview of heuristic solution methods in combinatorial optimization

Due to the computational complexity of most of the practical relevant optimization problems, heuristic methods form an important class of solution methods for such problems. In this course we give an overview of different classes of heuristic solution approaches and present examples of their application.

In detail, the following issues are treated:

  • Sampling based heuristics
  • Restricted dynamic programming
  • Truncated branch and bound/beam search
  • Relaxations/lower bounds
  • Evaluation techniques
  • Local search
  • Evolutionary methods
  • Hierarchical and decentralized approaches

Prerequisites

Basic knowledge (bachelor level) of analysis, linear algebra and linear programmin