Social Network Search for Global Optimization

Versione 1.0.0 (2,06 KB) da Siamak Talatahari
Social Network Search is developed as a new meta-heuristic algorithm.
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Social Network Search is developed as a new meta-heuristic algorithm that simulates the attempts of users in social networks to gain more popularity by modeling the moods of users in expressing their opinions. These moods are named Imitation, Conversation, Disputation, and Innovation, which are real-world behaviors of users in social networks. These moods are used as optimization operators and model how users are affected and motivated to share their new views.
The main paper is as:
Title: Social Network Search for Global Optimization
Authors: SIAMAK TALATAHARI, HADI BAYZIDI AND MEYSAM SARAEE
Journal: IEEE Acess 2021

Cita come

Siamak Talatahari (2024). Social Network Search for Global Optimization (https://www.mathworks.com/matlabcentral/fileexchange/94370-social-network-search-for-global-optimization), MATLAB Central File Exchange. Recuperato .

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Creato con R2021a
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1.0.0