Research on microseismic localization algorithm with global search and local optimization
Heliyon, 2023 A microseismic localization algorithm that combines global search and local optimization is proposed. The Fewer Conditions Trigger Difference (FCTD) objective function of global search and local optimization is constructed, the execution process of the ...
Yimin Song +4 more
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Local search for parallel optimization algorithms for high diminsional optimization problems [PDF]
MATEC Web of Conferences, 2018 Local search algorithms perform an important role when being employed with optimization algorithms tackling numerous optimization problems since they lead to getting better solutions.
Abd-Alsabour Nadia
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Efficient Local Search in Imaging Optimization Problems with a Hybrid Evolutionary Algorithm [PDF]
Journal of Systemics, Cybernetics and Informatics, 2005 The paper focuses on the efficiency of local search in a Hybrid evolutionary algorithm (HEA), with application to optimization problem frequently encountered in electronic imaging.
Igor Maslov
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Particle Swarm Optimization with Enhanced Global Search and Local Search
Journal of Intelligent Systems, 2017 In order to mitigate the problems of premature convergence and low search accuracy that exist in traditional particle swarm optimization (PSO), this paper presents PSO with enhanced global search and local search (EGLPSO).
Wang Jie, Li Hongwen
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A local search-based bi-objective optimization considering distance constraints
Nihon Kikai Gakkai ronbunshu, 2014 Conflicting interrelationships among objective functions are often encountered in real-world engineering design problems. If such exist in a multiobjective optimization problem, no unique solution can simultaneously minimize all of the objective ...
Yuki SATO +3 more
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Bayesian Optimization with Local Search [PDF]
, 2020 Global optimization finds applications in a wide range of real world problems. The multi-start methods are a popular class of global optimization techniques, which are based on the ideas of conducting local searches at multiple starting points. In this work we propose a new multi-start algorithm where the starting points are determined in a Bayesian ...
Yuzhou Gao, Tengchao Yu, Jinglai Li
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Multi-store collaborative delivery optimization based on Top-K order-split
PLoS ONE, 2023 Regarding the fulfillment optimization of online retail orders, many researchers focus more on warehouse optimization and distribution center optimization.
Yanju Zhang, Liping Ou, Jiaxu Liu
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A Hybrid Sparrow Search Algorithm of the Hyperparameter Optimization in Deep Learning
Mathematics, 2022 Deep learning has been widely used in different fields such as computer vision and speech processing. The performance of deep learning algorithms is greatly affected by their hyperparameters.
Yanyan Fan +5 more
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Local policy search with Bayesian optimization
CoRR, 2021 Reinforcement learning (RL) aims to find an optimal policy by interaction with an environment. Consequently, learning complex behavior requires a vast number of samples, which can be prohibitive in practice. Nevertheless, instead of systematically reasoning and actively choosing informative samples, policy gradients for local search are often obtained ...
Sarah Müller +2 more
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Approximate Local Search in Combinatorial Optimization [PDF]
SIAM Journal on Computing, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
James B. Orlin +2 more
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