Metaheuristic Algorithms in Modeling and Optimization

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@InCollection{Gandomi:2013:MASI,

• author = "Amir Hossein Gandomi and Xin-She Yang and Siamak Talatahari and Amir Hossein Alavi",
• title = "Metaheuristic Algorithms in Modeling and Optimization",
• editor = "Amir Hossein Gandomi and Xin-She Yang and Siamak Talatahari and Amir Hossein Alavi",
• booktitle = "Metaheuristic Applications in Structures and Infrastructures",
• publisher = "Elsevier",
• address = "Oxford",
• year = "2013",
• chapter = "1",
• pages = "1--24",
• keywords = "genetic algorithms, genetic programming, Nature-inspired algorithm, metaheuristic algorithms, modeling, optimisation",
• isbn13 = "978-0-12-398364-0",
• DOI = "doi:10.1016/B978-0-12-398364-0.00001-2",
• URL = "http://www.sciencedirect.com/science/article/pii/B9780123983640000012",
• abstract = "Metaheuristic algorithms have become powerful tools for modelling and optimisation. This chapter provides an overview of nature-inspired metaheuristic algorithms, especially those developed in the last two decades, and their applications. We will briefly introduce algorithms such as genetic algorithms, differential evolution, genetic programming, fuzzy logic, and most importantly, swarm-intelligence-based algorithms such as ant and bee algorithms, particle swarm optimization, cuckoo search, firefly algorithm, bat algorithm, and krill herd algorithm. We also briefly describe the main characteristics of these algorithms and outline some recent applications of these algorithms.",

}

Genetic Programming entries for A H Gandomi Xin-She Yang Siamak Talatahari A H Alavi

Citations