Camel Herds Algorithm: a New Swarm Intelligent Algorithm to Solve Optimization Problems

  • Ahmed T. Sadiq Al-Obaidi
  • Hasanen S. Abdullah
  • zied O. Ahmed

Abstract

Swarm Intelligence (SI) is a discipline that deals with artificial and naturalsystems which study the collective behaviors of social insects or animals. Camel HerdsAlgorithm (CHA) have been proposed as a new swarm intelligent algorithm in this work.The proposed algorithm depends on the behavior of the camel in the natural wild, takinginto consideration that there is a leader for each herd, food and water searchingdepending on humidity value with neighboring strategy. The Flexible Job Shop SchedulingProblem (FJSP) have been addressed as a case study to confirm the proposed algorithm.The trial result showed that the CHA is a good strategy to find the optimal solution inproblem space.

References

[1] Xin-She Yang, Zhihua Cui and Renbin Xiao; "Swarm
Intelligence and Bio-Inspired Computation Theory and
Applications"; Elsevier, First edition 2013
[2] MANSOUR A. AL-HAZIM and PAUL F. BRAIN; "A
Preliminary Study on the Behaviour of the Dromedary
(Camels dromedarius) in the Mid-western Region of
Saudi Arabia"; J. K. A. U.: Sci, vol. 5, pp. 71-76 (1413 A.H/
1993 A.D.)
[3] M. L. Pinedo, “Scheduling: Theory, Algorithms, and
Systems”, 3rd ed., Springer-Verlag, 2008.
[4]
Dr. Ahmed T. Sadiq Al-Obaidi and Samer Alaa Hussein;
"Two Improved Cuckoo Search Algorithm to solve
Flexible Job Shop Scheduling Problem"; International
Journal on Perceptive and Cognitive Computing; Vol 2,
No 2 (2016).
[5] Abir Ben Hmida, Mohamed Haouari, Marie-Jos_e Huguet
and Pierre Lopez ; "Discrepancy Search for the Flexible
Job Shop Scheduling Problem"; HAL Id: hal-00461981
Submitted on 8 Mar 2010
[6]
Guohui Zhang, Xinyu Shao; "An Effective Hybrid Particle
Swarm Optimization Algorithm for Multi-objective
Flexible Job-Shop Scheduling Problem"; Computers &
Industrial Engineering, Volume 56, Issue 4, May 2009,
Pages 1309–1318.
[7]
Jun-Qing Li, Quan-Ke Pan and Kai-Zhou Gao; "Pareto-
based Discrete Artificial Bee Colony Algorithm for Multi-
objective Flexible Job Shop Scheduling Problems"; The
International Journal of Advanced Manufacturing
Technology, August 2011, Volume 55, Issue 9, pp 1159–
1169.
[8] Graeme Phipps, Jacki Salkeld and Brad Walker; "Arabian
Camel Camelus dromedaries Camel idea: Mammalia";
Western Sydney Institute of TAFE, Richmond; Date of
Preparation: 29/07/08
[9] Falah K. Al-Ani; "Camel Management and Diseases"; Dar
Ammar Book Publisher 2004.
[10] Hurink E., Jurisch B. and Thole M.; “Tabu search for the
job shop scheduling problem with multi-purpose
machines”. Operations Research-Spektrum, 15:205–215;
1994.
[11] Fisher H. and Thompson G.L.; “Probabilistic learning
combinations of local job shop scheduling rules”. In
Industrial Scheduling, J.F. Muth and G.L. Thompson (Eds),
Englewood Cliffs, NJ: Prentice-Hall. p.225–251; 1993.
[12] Lawrence S.; “Supplement to resource constrained
project scheduling: an experimental investigation of
heuristic scheduling techniques”. GSIA, Carnegie Mellon
University, Pittsburgh, PA.; 1984.
Published
2017-05-22
How to Cite
T. SADIQ AL-OBAIDI, Ahmed; S. ABDULLAH, Hasanen; O. AHMED, zied. Camel Herds Algorithm: a New Swarm Intelligent Algorithm to Solve Optimization Problems. International Journal on Perceptive and Cognitive Computing, [S.l.], v. 3, n. 1, may 2017. ISSN 2462 - 229X. Available at: <http://journals.iium.edu.my/ijpcc/index.php/IJPCC/article/view/44>. Date accessed: 21 nov. 2017.
Section
Articles