User:P.ranjansingh68/SPIDER MONKEY OPTIMIZATION
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Spider Monkey Optimization
(SMO) is a recent addition in the field of nature inspired optimization algorithms developed by Bansal et al. [1] SMO is based on the intelligent foraging behaviour of spider monkeys. SMO can be broadly classified as a computational intelligence technique for global optimization.
Background
[edit]Before, designing a new swarm intelligence based algorithm, it must understand that whether a behaviour is swarm intelligence or not. Two approaches Division of Labour and Self-Organization are the necessary and sufficient conditions for obtaining intelligent swarming behaviours mentioned by Karaboga et.al.
Development of SMO
[edit]This page is under progress.
Algorithm
[edit]Main steps of Spider Monkey Optimization algorithm(SMO) Similar to the other population-based algorithms, SMO is a trial and error based collaborative iterative process.
There are two important parameter of this algorithm:
1) GlobalLeaderLimit.
2) LocalLeaderLimit.