Static drone placement by elephant herding optimization algorithm

Ivana Strumberger, Nebojsa Bacanin, Slavisa Tomic, Marko Beko, Milan Tuba

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Optimal placement of drones is a very challenging problem and it belongs to the group of hard optimization problems for which swarm intelligence algorithms were successfully applied. This paper presents an implementation of the recent elephant herding optimization algorithm for solving the static drone location problem. The objective of the model applied in this paper is to establish monitoring of all targets with the least possible number of drones. In empirical tests we used two problem instances: one with 30 uniformly distributed targets, and one with 30 clustered targets. The simulation results show that the elephant herding optimization algorithm performs well in covering targets for both instances of the problem, especially considering the number of drones that were deployed.

Original languageEnglish
Title of host publication2017 25th Telecommunications Forum, TELFOR 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Electronic)9781538630723
ISBN (Print)978-1-5386-3073-0
Publication statusPublished - 5 Jan 2018
Event25th Telecommunications Forum, TELFOR 2017 - Belgrade, Serbia
Duration: 21 Nov 201722 Nov 2017


Conference25th Telecommunications Forum, TELFOR 2017


  • Elephant herding optimization algorithm
  • metaheuristic optimization
  • static drone location problem
  • swarm intelligence


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