Open Access Open Access  Restricted Access Subscription Access

Performance Evaluation of Various Routing Algorithms Using Optimisation Methods

H. Fathima


Since nature displays a wide variety of diverse, constantly robust, sophisticated, and fascinating
phenomena, it is a huge and immense source of inspiration for addressing difficult and complex
problems in computer science. Metaheuristics called "nature inspired algorithms" solve
optimisation problems by mimicking nature, ushering in a new era of computing. This study
implements a new agent-based routing algorithm that makes use of optimisation techniques. The
various optimisation strategies utilised in the packet distribution between the networks include
crow search, whale, butterfly, donkey, and flower pollination. The process of routing involves
moving data through a network from source to destination. The simulation time of these
algorithms affects their result. The NS2 programming system, which is built on the fundamentals
of C, C++, and the TCL scripting language acquisition, is used to implement the investigations.
The results of the algorithm showed that the Butterfly algorithm is much better than the other
algorithms in the packet delivery between the networks.

Full Text:



. Peng, G,” Global artificial bee colony search algorithm for numerical function

optimization”. Seventh International Conference on Natural Computation (ICNC), pp.

–1283 in 2011.

. Shah, H, “G-HABC Algorithm for Training Artificial Neural Networks”. International

Journal of Applied Metaheuristic Computing , 3to 20 in 2012 [13]Shah, H.,

Ghazali, R., Nawi, “Hybrid Ant Bee Colony Algorithm for Volcano Temperature

Prediction”, pp. 453–465 in 2012.

. Kazharov, V. Kureichik, 2010. "Ant colony optimization algorithms for solving

transportation problems", Journal of Computer and Systems Sciences International, Vol.

No. 1. pp. 30–43.

. Abdel-Basset M, El-Shahat D, El-Henawy I, Sangaiah AK, Ahmed SH (2018) A novel

whale optimization algorithm for cryptanalysis in Merkle-Hellman Cryptosystem.

. Abdel-Basset M, Gunasekaran M, El-Shahat D, Mirjalili S (2018) A hybrid whale

optimization algorithm based on local search strategy for the permutation flow shop

scheduling problem. Fut Gen Comput Syst 85:129–145

. Abdulhamid SM, Latiff MSA, Idris I (2015) Tasks scheduling technique using league

championship algorithm for makespan minimization in IAAS cloud.

. Al-Janabi T, Al-Raweshidy H (2017) Efficient whale optimisation algorithm-based SDN

clustering for IoT focused on node density. In: 16th Annual Mediterranean on ad hoc

networking workshop (Med-Hoc-Net). IEEE, pp 1–6

. Alameer Z, Elaziz MA, Ewees AA, Ye H, Jianhua Z (2019) Forecasting gold price

fluctuations using improved multilayer perceptron neural network and whale

optimization algorithm. Resources Policy 61:250–260

. M. Wang and H. Chen, "Chaotic multi-swarm whale optimizer boosted support vector

machine for medical diagnosis", Appl. Soft Comput., vol. 88, Mar. 2020.

. X. Zhao, X. Zhang, Z. Cai, X. Tian, X. Wang, Y. Huang, et al., "Chaos enhanced

grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned

patients", Comput. Biol. Chem., vol. 78, pp. 481-490, Feb. 2019.

. H. Chen, Q. Zhang, J. Luo, Y. Xu and X. Zhang, "An enhanced bacterial foraging

optimization and its application for training kernel extreme learning machine", Appl. Soft

Comput., vol. 86, Jan. 2020.

. Y. Sun, G. G. Yen and Z. Yi, "IGD indicator-based evolutionary algorithm for

many-objective optimization problems", IEEE Trans. Evol. Comput., vol. 23, no. 2, pp.

-187, Apr. 2019.

. Abdelaziz A, Ali E, Elazim SA. Combined economic and emission dispatch

solution using flower pollination algorithm. Int J Electr Power Energy

Syst. 2016;80:264–274. doi: 10.1016/j.ijepes.2015.11.093.

. Abdelaziz A, Ali E, Elazim SA. Implementation of flower pollination algorithm

for solving economic load dispatch and combined economic emission dispatch problems

in power systems. Energy. 2016; 101:506–518. doi: 10.1016/

. Abdel-Basset M, Hezam I. A hybrid flower pollination algorithm for engineering

optimization problems. Int J Comput Appl. 2016;140:10–23.

. Abdel-Basset M, Shawky LA. Flower pollination algorithm: a comprehensive

review. Artif Intell Rev. 2018;52:2533–2557. doi: 10.1007/s10462-018-9624-4

. Abdel-Basset M, El-Shahat D, El-Henawy I, Sangaiah AK. A modified flower

pollination algorithm for the multidimensional knapsack problem: human-centric

decision making. Soft Comput. 2018;22:4221–4239. doi: 10.1007/s00500-017-2744

. Abdel-Raouf O, Abdel-Baset M, et al. A new hybrid flower pollination algorithm

for solving constrained global optimization problems. Int J Appl Oper Res-an Open

Access J. 2014;4:1–13.

. Abdel-Raouf O, El-Henawy I, Abdel-Basset M. A novel hybrid flower pollination

algorithm with chaotic harmony search for solving sudoku puzzles. Int J Mod Educ

Comput Sci. 2014;6:38. doi: 10.5815/ijmecs.2014.03.05.


  • There are currently no refbacks.