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Introduction to Meta-heuristic Optimization Algorithms
2019This chapter begins with a concise definition of the optimization problem and its parameters, along with a mathematical description of an optimization problem with continuous and discrete decision-making variables whose objective functions are employed in a standard form of an optimization problem along with equality and inequality constraints ...
Mohammad Kiani-Moghaddam +2 more
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Boxing Match Algorithm: a new meta-heuristic algorithm
Soft Computing, 2022Mehrab Tanhaeean +2 more
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Genetic Algorithm and Other Meta-Heuristics
2005Genetic algorithms have been applied in solving various types of large-scale, NP-hard optimization problems. Many researchers have been investigating its global convergence properties using Schema Theory, Markov Chain, etc. A more realistic approach, however, is to estimate the probability of success in finding the global optimal solution within a ...
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Local search and meta-heuristic algorithms
2020Suboptimal schedules for intractable time-dependent scheduling problems may be found by using various algorithms. In this chapter, closing the fifth part of the book, we consider local search and meta-heuristic algorithms.
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Metrics for meta-heuristic algorithm evaluation
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2004By adopting best practices from quality management in industry, metrics as well as test cycle are proposed to evaluate the performance of meta-heuristic algorithm.
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Competitive Learning: A New Meta-Heuristic Optimization Algorithm
International Journal on Artificial Intelligence Tools, 2018This work proposes a new powerful meta-heuristic optimization algorithm in education process called Competitive Learning (CLA). The algorithm is benchmarked on 8 well-known test functions, and the results are verified by a comparative study with some meta-heuristic optimization methods including: Imperialist Competitive Algorithm (ICA), Teaching ...
Afshin Afroughinia +1 more
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New Surrogate Approaches Applied to Meta-Heuristic Algorithms
2020Surrogate can be defined as a mechanism capable of learning the behavior of a given objective function. As it is a regression problem, machine learning (ML) models are natural candidates to solve it. However, there is a lack of works comparing different machine learning techniques employed as surrogates.
Joel Alves de Oliveira +4 more
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Meta-heuristics Algorithms: A survey
International Journal of Engineering Trends and Technology, 2019Shereen Zaki, Abd El-Nasser H. Zaied
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Meta-Heuristics Algorithm for Computer Communications
Communication technology's advancement has revolutionized industries and shaped social norms by changing how we connect and communicate. Every technological development, from the earliest days of telegraphy to the present day of wireless connectivity and high-speed internet, has brought the world closer together.Krithikaa Venket +2 more
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A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models
Renewable and Sustainable Energy Reviews, 2021Shuijia Li, Wenyin Gong, Qiong Gu
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