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Metaheuristics “In the Large” [PDF]
European Journal of Operational Research, 2022 Después de décadas de mejora sostenida, la metaheurística es una de las grandes historias de éxito de la investigación de optimización. Sin embargo, para que la investigación en metaheurística evite la fragmentación y la falta de reproducibilidad, existe una necesidad apremiante de una infraestructura científica y computacional más sólida para apoyar ...
Jerry Swan +15 more
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Metaheuristics for pharmacometrics [PDF]
CPT: Pharmacometrics & Systems Pharmacology, 2021 AbstractMetaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature‐inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be particularly flexible and useful in solving complicated optimization problems in computer ...
Kim, Seongho +4 more
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Frontiers in Neuroinformatics, 2023 IntroductionRegression and classification are two of the most fundamental and significant areas of machine learning.MethodsIn this paper, a radial basis function neural network (RBFNN) based on an improved black widow optimization algorithm (IBWO) has ...
Hui Liu +9 more
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An Overview of the Concepts, Classifications, and Methods of Population Initialization in Metaheuristic Algorithms [PDF]
Journal of Advances in Computer Engineering and Technology, 2021 Metaheuristic algorithms are typically population-based random search techniques. The general framework of a metaheuristic algorithm consisting of its main parts.
Mohammad Hassanzadeh, farshid keynia
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An Enhanced Discrete Symbiotic Organism Search Algorithm for Optimal Task Scheduling in the Cloud
Algorithms, 2021 Recently, cloud computing has begun to experience tremendous growth because government agencies and private organisations are migrating to the cloud environment.
Suleiman Sa’ad +4 more
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Training Spiking Neural Networks with Metaheuristic Algorithms
Applied Sciences, 2023 Taking inspiration from the brain, spiking neural networks (SNNs) have been proposed to understand and diminish the gap between machine learning and neuromorphic computing.
Amirhossein Javanshir +3 more
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Buildings, 2023 This paper presents a multi-objective optimization of steel trusses using direct analysis. The total weight and the inter-story drift or displacements of the structure were two conflict objectives, while the constraints relating to strength and ...
Truong-Son Cao +4 more
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Biomimetics, 2023 A new metaheuristic algorithm called green anaconda optimization (GAO) which imitates the natural behavior of green anacondas has been designed. The fundamental inspiration for GAO is the mechanism of recognizing the position of the female species by the
Mohammad Dehghani +2 more
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DGTTSSA: Data Gathering Technique Based on Trust and Sparrow Search Algorithm for WSNs
Sensors, 2023 Wireless Sensor Networks (WSNs) have been successfully utilized for developing various collaborative and intelligent applications that can provide comfortable and smart-economic life. This is because the majority of applications that employ WSNs for data
Walid Osamy +3 more
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Structure and metaheuristics [PDF]
Proceedings of the 8th annual conference on Genetic and evolutionary computation, 2006 Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems. The reason for that, however, remains unclear. A framework for a theory of metaheuristics crucially depends on a formal representative model of such algorithms.
Yossi Borenstein, Riccardo Poli
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