Comparison of Ant Colony Optimization and Artificial Bee Colony Algorithms for Solving Electronic Support Search Dwell Scheduling Problem

Erkut O., HARDALAÇ F.

15th Turkish National Software Engineering Symposium, UYMS 2021, Virtual, Izmir, Türkiye, 17 - 19 Kasım 2021 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/uyms54260.2021.9659666
  • Basıldığı Şehir: Virtual, Izmir
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Ant Colony Optimization Algorithm, Artificial Bee Colony Algorithm, Combinatorial Optimization, Electronic Support, Scheduling, TASKS
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2021 IEEE.Electronic support search dwell scheduling is a combinatorial optimization problem which appears when the dwells overlapping on frequency domain are assigned to different receivers and required to be executed simultaneously by the receivers that are on a single electronic support platform. Overlapping the dwells on time domain provides sensor fusion ability and improves the detection performance of the system against target radar systems. In this paper, dwell sets of the receivers are scheduled to solve electronic support search dwell scheduling problem with two meta-heuristic swarm intelligence algorithms: Ant Colony Algorithm and Artificial Bee Colony Algorithm. Simulation results show that while both algorithms are capable of solving the problem, Ant Colony Algorithm provides a solution roughly 43% faster with a limit on number of iterations and Artificial Bee Colony Algorithm provides roughly 30% quicker and 26% more consistent solution with a limit on maximum acceptable cost.