Results 11 to 20 of about 45,948 (211)
A Multiple-Search Multi-Start Framework for Metaheuristics for Clustering Problems
IEEE Access, 2020 Metaheuristic algorithms have been widely used as an effective and efficient way for solving various complex optimization problems; there is, however, plenty of room for improvement.
Kai-Cheng Hu +2 more
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Firefly Algorithms for Multimodal Optimization [PDF]
, 2009 Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications.
Yang, Xin-She
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Firefly Algorithm: Recent Advances and Applications [PDF]
, 2013 Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with diverse ...
He, Xingshi, Yang, Xin-She
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Flood algorithm: a novel metaheuristic algorithm for optimization problems [PDF]
PeerJ Computer ScienceMetaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods.
Ramazan Ozkan, Ruya Samli
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MetaCluster: An open-source Python library for metaheuristic-based clustering problems
SoftwareX, 2023 Clustering, based on metaheuristic algorithms, is a rapidly developing field. Its goal is to use these methods to reframe clustering issues as optimization problems. In this study, we propose an open-source library named MetaCluster.
Nguyen Van Thieu +2 more
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Metaheuristic Algorithms for Convolution Neural Network [PDF]
, 2016 A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry.
Arymurthy, Aniati Murni +2 more
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On the use of biased-randomized algorithms for solving non-smooth optimization problems [PDF]
, 2020 Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory ...
Ferrer Biosca, Albert +4 more
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Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications [PDF]
, 2011 Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resources and appropriate constraints.
A. Chatterjee +23 more
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Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, 2023 Many optimization problems are complex, challenging and take a significant amount of computational effort to solve. These problems have gained the attention of researchers and they have developed lots of metaheuristic algorithms to use for solving these ...
Aydın Sipahioğlu, İslam Altın
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Two-Stage Eagle Strategy with Differential Evolution [PDF]
, 2012 Efficiency of an optimization process is largely determined by the search algorithm and its fundamental characteristics. In a given optimization, a single type of algorithm is used in most applications.
Deb, Suash, Yang, Xin-She
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