Fitness Based Position Update in Spider Monkey Optimization Algorithm | Zendy

Sandeep Kumar | Zendy; Rajani Kumari | Zendy; Vivek Kumar Sharma | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Fitness Based Position Update in Spider Monkey Optimization Algorithm

Author(s) -

Sandeep Kumar,

Rajani Kumari,

Vivek Kumar Sharma

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.08.504

Subject(s) - computer science , position (finance) , benchmark (surveying) , algorithm , convergence (economics) , swarm behaviour , swarm intelligence , mathematical optimization , particle swarm optimization , artificial intelligence , mathematics , geodesy , finance , economic growth , economics , geography

pider Monkey Optimization (SMO) technique is most recent member in the family of swarm optimization algorithms.SMO algorithm fall in class of Nature Inspired Algorithm (NIA). SMO algorithm is good in exploration and exploitation of local search space and it is well balanced algorithm most of the times. This paper presents a new strategy to update position of solution during local leader phase using fitness of individuals. The proposed algorithm is named as Fitness based Position Update in SMO (FPSMO) algorithm as it updates position of individuals based on their fitness. The anticipated strategy enhances the rate of convergence. The planned FPSMO approach tested over nineteen benchmark functions and for one real world problem so as to establish superiority of it over basic SMO algorithm

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research