Solving Flexible Job Shop Scheduling Problem Using Meerkat Clan Algorithm

  • Ahmed T. Sadiq Department of Computer Science, Technology University, Baghdad, Iraq
  • Hasanen S. . Abdullah Department of Computer Science, Technology University, Baghdad, Iraq
  • Zied O. Ahmed Department of Computer Science, College of Science, Mustansiriyah University, Baghdad, Iraq
Keywords: Meerkat Clan Algorithm, Flexible job shop scheduling, Swarm Intelligence, Cuckoo Search Algorithm, Artificial Fish Search Algorithm, Camel Herd Algorithm

Abstract

Meerkat Clan Algorithm (MCA) that is a swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. Meerkat has some behaviour. Sentry, foraging, and baby-sitter are the behaviour used to build this algorithm through dividing the solution sets into two sets, all the operations are performed on the foraging set. The sentry presents the best solution. The Flexible Job Shop Scheduling Problem (FJSSP) is vital in the two fields of generation administration and combinatorial advancement. In any case, it is very hard to accomplish an ideal answer for this problem with customary streamlining approaches attributable to the high computational unpredictability. Most scheduling problem are mind boggling combinatorial problem and exceptionally hard to settle. The experimental result that compare with Cuckoo Search algorithm, Artificial Fish Search Algorithm, and Camel Herd Algorithm show that the MCA can find optimal solution because it provides a good strategy.

Published
2018-04-29
How to Cite
SadiqA. T., . AbdullahH. S., & AhmedZ. O. (2018). Solving Flexible Job Shop Scheduling Problem Using Meerkat Clan Algorithm. Iraqi Journal of Science, 59(2A), 754-761. Retrieved from http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/251
Section
Computer Science