DocumentCode :
3575397
Title :
Competition over Resources: A New Optimization Algorithm Based on Animals Behavioral Ecology
Author :
Mohseni, Sina ; Gholami, Reza ; Zarei, Niloofar ; Zadeh, Arash Roomi
Author_Institution :
Fac. of Electr. Eng., Noshirvani Univ. of Technol., Babol, Iran
fYear :
2014
Firstpage :
311
Lastpage :
315
Abstract :
In the recent years, many heuristic optimization algorithms have been developed. A majority of these heuristic algorithms have been derived from the behavior of biological or physical systems in nature. In this paper, we propose a new optimization algorithm based on competitive behavior of animal groups. In the proposed algorithm, the whole population is divided into a number of groups. In each group, the best searching agent spreads its children in its owned territory. Any group which is not able to find rich resources will be eliminated form competition. The competition gradually results in an increase in population of wealthy group which gives a fast convergence to proposed optimization algorithm. In the following, after a detailed explanation of the algorithm and pseudo code, we compare it to other existing algorithms, including genetics and particle swarm optimizations. Applying the proposed algorithm on various benchmark cost functions, shows faster and superior results compared to other optimization algorithms.
Keywords :
behavioural sciences computing; ecology; optimisation; software agents; animal groups; animals behavioral ecology; competitive behavior; cost functions; heuristic algorithms; heuristic optimization algorithms; particle swarm optimizations; physical systems; pseudo code; searching agent; Algorithm design and analysis; Animals; Benchmark testing; Heuristic algorithms; Optimization; Sociology; Statistics; animals behavioral ecology; nature inspired algorithm; optimization algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Networking and Collaborative Systems (INCoS), 2014 International Conference on
Print_ISBN :
978-1-4799-6386-7
Type :
conf
DOI :
10.1109/INCoS.2014.55
Filename :
7057107
Link To Document :
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