Results 31 to 40 of about 46,625 (244)
Proposal and Comparative Study of Evolutionary Algorithms for Optimum Design of a Gear System [PDF]
, 2019 This paper proposes a novel metaheuristic framework using a Differential Evolution (DE) algorithm with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II).
Frutos, Mariano +3 more
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Applied Sciences, 2022 Four-bar linkages are one of the most widely used mechanisms in industries. This paper presents a comparative study on the accuracy and efficiency of the optimum synthesis of path-generating four-bar linkages using five metaheuristic optimization ...
Yaw-Hong Kang, Jau-Wen Lin, Wei-Chen You
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Multi-Objective Big Data Optimization with jMetal and Spark [PDF]
, 2017 Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi ...
A Cabanas-Abascal +11 more
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Why Tuning the Control Parameters of Metaheuristic Algorithms Is So Important for Fair Comparison?
Mendel, 2020 Although metaheuristic optimization has become a common practice, new bio-inspired algorithms often suffer from a priori ill reputation. One of the reasons is a common bad practice in metaheuristic proposals.
Anezka Kazikova +2 more
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A novel metaheuristic optimization algorithm: the monarchy metaheuristic
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2019 In this paper, we introduce a novel metaheuristic optimization algorithm named the monarchy metaheuristic (MN). Our proposed metaheuristic was inspired by the monarchy government system. Unlike many other metaheuristics, it is easy to implement and does not need a lot of parameters. This makes it applicable to a wide range of optimization problems.
Ibtissam AHMIA, Méziane AÏDER
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Next Generation Metaheuristic: Jaguar Algorithm
IEEE Access, 2018 Metaheuristic algorithms are implemented to solve optimization problems and have recently received significant research attention. Metaheuristic algorithms rely primarily on two properties, exploration, and exploitation.
Yao-Hsin Chou +3 more
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Algorithms, 2021 The integration of different energy resources from traditional power systems presents new challenges for real-time implementation and operation. In the last decade, a way has been sought to optimize the operation of small microgrids (SMGs) that have a ...
Andrés Angulo +5 more
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Using metaheuristic algorithms remotely via ROS [PDF]
Proceedings of the 9th annual conference on Genetic and evolutionary computation, 2007 Jose Garcia-Nieto Dpto. Lenguajes y Ciencias de la Computacion E.T.S. Ingenieria Informatica University of Malaga, Spain jnieto@lcc.uma.es Enrique Alba Dpto. Lenguajes y Ciencias de la Computacion E.T.S. Ingenieria Informatica University of Malaga, Spain eat@lcc.uma.es Francisco Chicano Dpto. Lenguajes y Ciencias de la Computacion E.T.S.
García Nieto, José Manuel +2 more
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Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems
International Journal of Computational Intelligence Systems, 2021 This paper suggests five new contributions with respect to the state-of-the-art. First, the optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs) is carried out using a ...
Radu-Emil Precup +4 more
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Implementing Metaheuristic Optimization Algorithms with JECoLi [PDF]
2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009 This work proposes JECoLi - a novel Java-based library for the implementation of metaheuristic optimization algorithms with a focus on Genetic and Evolutionary Computation based methods. The library was developed based on the principles of flexibility, usability, adaptability, modularity, extensibility, transparency, scalability, robustness and ...
Evangelista, Pedro +2 more
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