NDLI: Geological Optimization

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Geological Optimization

Content Provider	Scilit
Author	Cruz, Pedro Ponce Gutiérrez, Arturo Molina Ramírez-Mendoza, Ricardo A. Flores, Efraín Méndez Espinoza, Alexandro Antonio Ortiz Silva, David Christopher Balderas
Copyright Year	2020
Description	Metaheuristic algorithms are classified into principal categories: evolutionary based, physical based, swarm based, and human behavior based. First, evolutionary-based algorithms imitate the natural biological evolution and/or social behavior of species. Second, physical-based algorithms have some characteristics of the laws and forces of physics such as gravitational, electromagnetic, and inertia. Third, swarm-based algorithms use the collective intelligence from organisms in a community sharing local information with other individuals, such as ants and bees. The most known methods include particle swarm optimization, monkey search algorithm, bat algorithm, cuckoo search, wolf pack search algorithm, firefly algorithm, artificial bee colony, and the ant colony optimization. Finally, the last category is based on the human behavior in different situations or activities, such as teaching-learning-based optimization, neighborhood searching, sociopolitically motivated strategies, musicians harmony calibration for melodies, and mimicking team sports competitions. Book Name: A Practical Approach to Metaheuristics Using LabVIEW and MATLAB®
Related Links	https://content.taylorfrancis.com/books/download?dac=C2019-0-00305-3&isbn=9780429324413&doi=10.1201/9780429324413-8&format=pdf
Ending Page	86
Page Count	10
Starting Page	77
DOI	10.1201/9780429324413-8
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-06-08
Access Restriction	Open
Subject Keyword	Book Name: A Practical Approach To Metaheuristics Using Labview and Matlab® Cybernetical Science Optimization Algorithms Evolutionary Colony Based On the Human Behavior
Content Type	Text
Resource Type	Chapter

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