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An Improved Artificial Bee Colony ( IABC ) Algorithm for Numerical Function Optimization
| Content Provider | Semantic Scholar |
|---|---|
| Author | Naveena, S. Sathiya Malathy, Sup C. Saranya, D. Kumar, P. Rajesh |
| Copyright Year | 2015 |
| Abstract | This paper proposes an Improved Artificial Bee Colony (IABC) algorithm by introducing the Newtonian Law of Universal Gravitation between the employed bee and onlooker bee. The Universal Gravitation considers the fitness value of the employed bee that is picked by applying the roulette wheel selection as well as the fitness value of the randomly selected employed bees. Since the proposed modification makes the onlooker bee to perform neighborhood search using more than one employed bee it widens the exploration capability of the algorithm. The performance of the proposed IABC is tested using six bench mark functions. From the simulation result it is found the exploration ability of the proposed IABC is not constrained through a narrow zone and produces better results without getting struck in to the local optima when compared with simple ABC. KeywordsNumerical Optimization, Swarm Intelligence, Artificial Bee Colony, Newtonian Law of Gravitation |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijaiet.com/images/Papers/An%20Improved%20Artificial%20Bee%20Colony%20(IABC)%20Algorithm%20for%20Numerical%20Function%20Optimization.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
