Socio-inspired Optimization Metaheuristics: A Review

摘要: The chapter attempts to review the recent literature in upcoming area of socio-inspired metaheuristics. These optimization methodologies are a novel subbranch popular Evolutionary algorithms under class nature-inspired for optimization. seeks inspiration from human behavior seen during course social and cultural interactions with others. A being exhibits natural inherent tendencies competitive behavior, collaborate, work together interact socially culturally. All such behaviors help an individual learn imbibe other humans, resulting them adapt improve their own due time. This tendency observed humans serves as motivation were agents optimizer algorithm toward achieving some shared goals. finds strength fact that individuals tend evolve faster through setup than just biological evolution based on inheritance alone. In article, authors introduce summarize existing algorithms, sources inspiration, basic functioning. Additionally, also sheds light limitations strengths each these optimizers discussed article. problem domains which have been successfully applied is presented. note most developed this nature inspire new still evolving, thus promising scope domain.