Results 41 to 50 of about 50,815 (253)
An Improved Bat Algorithm with Grey Wolf Optimizer for Solving Continuous Optimization Problems [PDF]
Journal of Advances in Computer Engineering and Technology, 2020 Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near ...
narges jafari +1 more
doaj
The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms [PDF]
, 2020 open access articleWe present Stochastic Optimisation Software (SOS), a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms.
Caraffini, Fabio, Iacca, Giovani
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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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Analytical versus Metaheuristic Methods to Extract the Photovoltaic Cells and Panel Parameters
International Journal of Photoenergy, 2021 The parameters of the photovoltaic cells and panels are very important to forecast the power generated. There are a lot of methods to extract the parameters using analytical, metaheuristic, and hybrid algorithms.
Daniel T. Cotfas +3 more
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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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KPLS Optimization With Nature-Inspired Metaheuristic Algorithms
IEEE Access, 2020 Kernel partial least squares regression (KPLS) is a technique used in several scientific areas because of its high predictive ability. This article proposes a methodology to simultaneously estimate both the parameters of the kernel function and the ...
Jorge Daniel Mello-Roman +1 more
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Free Lunch or No Free Lunch: That is not Just a Question?
, 2012 The increasing popularity of metaheuristic algorithms has attracted a great deal of attention in algorithm analysis and performance evaluations. No-free-lunch theorems are of both theoretical and practical importance, while many important studies on ...
Yang, Xin-She
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On the Neutrality of Flowshop Scheduling Fitness Landscapes [PDF]
, 2011 Solving efficiently complex problems using metaheuristics, and in particular local searches, requires incorporating knowledge about the problem to solve. In this paper, the permutation flowshop problem is studied.
C.O. Wilke +15 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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Neural based hybrid metaheuristic technique for computing rotating transport of Falkner-Skan flow
Alexandria Engineering Journal, 2018 In present analysis we are focused on neural based hybrid metaheuristic technique for computing rotating transport of Falkner-Skan flow. We incorporate modeling of present problem using artificial neural network (ANN).
Z. Iqbal +3 more
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