Source code and algorithm description for SMO algorithm in Wireless Sensor Networks (WSN)CH_prob_i = [0.9 * (fitness_i/fitness_max) + 0.1] * P (1)
Abstract: The aim of this letter is to introduce and use the spider monkey optimization (SMO) as an optimization technique for the electromagnetics and antenna communities. The SSO algorithm is based on the simulation of cooperative behavior of social-spiders. The SMO is a new swarm intelligence technique that models the foraging behavior of spider monkeys. Access options Buy single article. The software contains a main function SSO.m and five auxiliary functions (FeMove.m, Griewank.m, MaMove.m, Mating.m and Survive.m). Therefore, the proposed strategy broadly classified as inspiration from the intelligent foraging behavior of fission-fusion social structure based animals.Social behavior of spider monkeys inspires authors to develop an stochastic optimization technique that mimics the foraging behavior of spider monkeys. Created with Swarm intelligence is a fascinating area for the researchers in the field of optimization. The animals which follow fission-fusion social systems, initially work in a large group and based on need after some time, they divide themselves in smaller groups led by an adult female for foraging.
The SSO algorithm is based on the simulation of cooperative behavior of social-spiders. Spider Monkey Optimization Routing Protocol (source code, algorithm description, publications and etc) Hashes for python-spidermonkey-0.0.10.tar.gz; Algorithm Hash digest; SHA256: 5409546a68b794a398f8598eddfeb4274559376c54c84c8b752798391712d889: Copy MD5 A swarm optimization algorithm inspired in the behavior of the social-spiderA swarm optimization algorithm inspired in the behavior of the social-spiderA swarm optimization algorithm inspired in the behavior of the social-spider %PDF-1.4 stream SMO is a population based stochastic meta-heuristic. Using SpiderMonkey Introduction to the JavaScript shell Documentation of the command-line JavaScript shell, js. bat algorithm (BA), which can deal with nonlinear, global optimization problems. For example, members of a group are separated from the main group in order to hunt or forage for food during the day, Thus the proposed optimization algorithm which is based on foraging behavior of spider monkeys can be explained better in terms of FFSS.
SSO considers two search agents (spiders): male and female. SMO particularly is determined to be the superior in the category of swarm intelligent approaches. Spider Monkey Optimization (SMO) algorithm (History and main idea) Spider Monkey Optimization (SMO) algorithm is a new swarm intelligence algorithm proposed in 2014 by J. C. Bansal et. Several algorithms arising from such models have been proposed to solve a wide range of complex optimization problems. Spider Monkey Optimization Algorithm for Numerical Optimization 3 parent group can fission into smaller subgroups or individuals to adapt the environmental or social circumstances. Spider Monkey Optimization Routing Protocol (source code, algorithm description, publications and etc) To show the efficiency of the SMO, different examples are presented, and … �9� Following are the key features of the FFSS. In order to illustrate the proficiency and robustness of the proposed approach, it is compared to other well-known evolutionary methods. In this paper, a novel swarm algorithm called the Social Spider Optimization (SSO) is proposed for solving optimization tasks.
In this paper, a novel swarm algorithm called the Social Spider Optimization (SSO) is proposed for solving optimization tasks. The Spider Monkey Optimization (SMO) algorithm.
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