A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Yadav, Himani
- A Survey:Whale Optimization Algorithm for Route Optimization Problems
Authors
1 Department of CSE, NIIST, RGPV, Bhopal, IN
Source
Wireless Communication, Vol 9, No 5 (2017), Pagination: 105-108Abstract
This work presents wireless optimization with the help of a Meta heuristic algorithm from the group of swarm algorithms named as Whale Optimization Algorithm (WOA). It is a multi-objective algorithm that can be used in solving more than one problem. This algorithm copies the hunting behaviour of the one of the whale species named as humpback whale. Whale optimization algorithm copies the spiral net technique, in which the whale creates a spiracle net of bubbles for encircling the pray and then find the prey either randomly or whale have to apply best find strategy to find the moving prey. This algorithm can be used in many fields like ad-hoc, wireless network, power electronics, and classical engineering problems. But here in this paper it is going to apply on route finding Problem in wireless network. Where the wireless network require to find the location of moving device and also needed to find the optimal path from one device to another for data delivery. In such type of problems Whale optimization algorithm can produce batter results then tradition algorithm.
Keywords
Ad Hoc Network, Meta Heuristic, Swarm Techniques, Whale Optimization.
References
- S. Mirjalili, A. Lewis, The Whale Optimization Algorithm, Advances in Engineering.Software.in.press,.2016,.DOI:http://dx.doi.org/10.1016/j.advengsoft.2016.01.008
- X. Li, A new intelligent optimization-artificial fish swarm algorithm Doctor Thesis, Zhejiang University of Zhejiang, China, 2003.
- M. Roth, W. Stephen, Termite: A swarm intelligent routing algorithm for mobilewireless Ad-Hoc networks, in: Stigmergic Optimization, Springer Berlin Heidelberg, 2006, pp. 155-184.
- A. Kaveh , N. Farhoudi, A new optimization method: Dolphin echolocation, Advances in Engineering Software, 59, p.53-70, May, 2013 [doi>10.1016/j.advengsoft.2013.03.004
- B. Zeng, Y. Dong, An improved harmony search based energyefficientrouting algorithm for wireless sensor networks, Applied Soft Computing, 41 (2016) 135-147.
- Hongping Hu, Yanping Bai, and Ting Xu Improved whale optimization algorithms based on inertia weights and theirs applications, INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING Volume 11, 2017.
- Mohammad Rohani, GholamaliShafabakhsh, Abdolhosein Haddad and EhsanAsnaashariThe workflow planning of construction sites using whale optimization algorithm (WOA), The Turkish Online Journal of Design, Art and Communication, 10.7456/1060NVSE/107.
- X.N.Li,G.F.Yang,“Artificial bee colony algorithm with memory, ”Applied Soft Computing, vol.41,pp.362-372,2016.
- Bing Zeng , Liang Gao and Xinyu Li ,Whale swarm algorithm for function optimization.
- K.C. Tan, Y. Chew, L.H. Lee, A hybrid multi-objective evolutionary algorithm for solving truck and trailer vehicle routing problems, European Journal of Operational Research, 172 (2006) 855-885.
- Y. Tan, Y. Zhu, Fireworks algorithm for optimization, Springer, 2010.
- C. Prodhon A hybrid evolutionary algorithm for the periodic location-routing problem. European Journal of Operational Research. 2011 Apr; 210(2):204–12.
- Cellular Genetic Algorithms. IJCSNS International Journal of Computer Science and Network Security. 2012 Feb; 12(2).
- C Selvaraj, R Siva Kumar, M Karnan. A survey on application of bio-inspired algorithms. International Journal of Computer Science and Information Technologies. 2014; 5(1):366–70.
- CBlum, ARoli. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys. 2003 Sep; 35(3):268–308.
- CArchetti, . An optimization-based heuristic for the split delivery vehicle routing problem. Journal Transportation Science archive. 2008 Feb; 42(1):22–31.