Skip to main content
The name “Hippopotamus Optimization” (HO) is inspired by the social and territorial behaviors of hippos in the wild. The algorithm models these behaviors to solve complex optimization problems like VM placement.

​
The Analogy

Here’s a breakdown of the analogy:
  • Hippos as Solutions: Each “hippopotamus” in the algorithm represents a potential solution to the VM placement problem.
  • Territory as the Search Space: The environment where the hippos live and interact represents the search space of all possible VM-to-host mappings.
  • Leader Hippo: The strongest hippo in the herd, which guides the others, is analogous to the best solution found so far in the optimization process.
  • Prey Dynamics and Random Walks: The algorithm incorporates elements of exploration and exploitation, inspired by how hippos interact with their environment and other animals. This is reflected in the position update equation, which includes factors for leader influence, prey influence, and random walks.

​
Reference

The Hippopotamus Optimization algorithm was introduced in the following paper: