KU Metaheuristics

Metaheuristics are general-purpose methods to find high-quality solutions to difficult optimization problems at relatively low computational cost. They are particularly attractive in the efficient and effective solution of logistic decision problems in supply chains, transportation, telecommunications, vehicle routing and scheduling, manufacturing and machine scheduling, timetabling, sports scheduling, facility location and layout, and network design, among other areas. In this course you will get the fundamental tools for designing, tuning, and testing metaheuristics for hard combinatorial optimization problems. >

 Course content

  • Introduction to the analysis of algorithms and complexity theory
  • Local search-based methods
  • Nature-inspired metaheuristics
  • Construction-based metaheuristics


  • M. Gendreau and J.-Y. Potvin (2010), editors, Handbook of Metaheuristics, 2nd edition, Springer, 648 pages.
  • E. K. Burke and G. Kendall (2014), editors, Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, 2nd edition, Springer, 716 pages.
  • H. H. Hoos and T. Stützle (2005), Stochastic Local Search: Foundations and Applications, Elsevier, 658 pages.