Title :
Adaptive fuzzy influence function for cultural algorithm
Author_Institution :
Department of Computer Science, Islamic Azad University-South Tehran Branch, Tehran, Iran
Abstract :
Cultural Algorithm is an evolutionary model inspired by the cultural evolution process which employs a basic set of knowledge sources, each related to knowledge observed in various social species. This study presents a modified version of cultural algorithm which benefits from adaptive fuzzy system. The adaptive fuzzy system is implemented as an extension of the influence function in cultural algorithm which provides a guideline in which individuals can access the suitable knowledge source. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. The proposed algorithm is much like what the human brain does that is to predict knowledge source bases of some knowledge it has gained from the previous updates. Finally the enhanced cultural algorithm evaluated on a problem in Engineering Design, the "Pressure Vessel Problem". For this problem, it is shown that the enhanced cultural algorithm with the adaptive fuzzy system outperforms the cultural algorithm, cultural algorithm with Social Fabric, and some optimization algorithms including Genetic Algorithm, and particle swarm optimization.
Keywords :
"Fuzzy systems","Sociology","Statistics","Optimization","Adaptive systems","Cultural differences","Algorithm design and analysis"
Conference_Titel :
SAI Intelligent Systems Conference (IntelliSys), 2015
DOI :
10.1109/IntelliSys.2015.7361216