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Author Correction: Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems. [PDF]
Sci RepPremkumar M +7 more
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Metaheuristic Optimization Algorithms
2021In this introductory chapter, specific state-of-the-art metaheuristic optimization algorithms are outlined. The presented algorithms belong to the broad trajectory-based and population-based categories, and they are particularly selected as they constitute the building blocks of algorithm portfolios presented in the forthcoming chapters.
Dimitris Souravlias +3 more
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Metaheuristic Clustering Algorithms
2020Metaheuristic algorithms are well-known optimization tools which have been used in many applications including those in data mining. In particular, these algorithms are well suited for solving nonconvex clustering problems since they are able to find global solutions whereas the traditional clustering algorithms such as k-means can only guarantee ...
Adil Bagirov +2 more
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Brick-Up Metaheuristic Algorithms
2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), 2016Metaheuristic algorithms have been a very important topic in computer science since the start of evolutionary computing the Genetic Algorithms 1950s. By now these metaheuristic algorithms have become a very large family with successful applications in industry. A challenge which is always pondered on, is finding the suitable metaheuristic algorithm for
Qun Song, Simon Fong
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Metaheuristic anopheles search algorithm
Evolutionary Intelligence, 2020Today, various optimization problems have been solved using different optimization techniques such as linear programming, nonlinear programming and dynamic programming. These methods mainly try to find optimal solution in the proximity of starting point.
Hossein Baloochian +2 more
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Automated Design of Metaheuristic Algorithms
2018The design and development of metaheuristic algorithms can be time-consuming and difficult for a number of reasons including the complexity of the problems being tackled, the large number of degrees of freedom when designing an algorithm and setting its numerical parameters, and the difficulties of algorithm analysis due to heuristic biases and ...
Stützle, Thomas +1 more
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Fuzzy optimization and metaheuristic algorithms
Babylonian Journal of Mathematics, 2023Fuzzy optimization and metaheuristic algorithms are two important fields in computational intelligence. Fuzzy optimization deals with the optimization of systems or processes that involve fuzzy sets or fuzzy logic, while metaheuristic algorithms are a class of optimization algorithms that are designed to solve difficult problems by mimicking natural ...
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Chaos Embedded Metaheuristic Algorithms
2014In nature complex biological phenomena such as the collective behavior of birds, foraging activity of bees or cooperative behavior of ants may result from relatively simple rules which however present nonlinear behavior being sensitive to initial conditions.
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Introduction: Optimization and Metaheuristics Algorithms
2020Present chapter embodies an introductory overview of optimization and metaheuristic algorithms. An optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function.
Padam Singh, Sushil Kumar Choudhary
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