Results 41 to 50 of about 2,269,659 (185)
Improved teaching learning based optimization for global function optimization [PDF]
Decision Science Letters, 2013 Teaching–Learning-Based Optimization (TLBO) is recently being used as a new, reliable, accurate and robust optimization technique scheme for global optimization over continuous spaces.
Suresh Chandra Satapathy, Anima Naik
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An informational approach to the global optimization of expensive-to-evaluate functions
, 2007 In many global optimization problems motivated by engineering applications, the number of function evaluations is severely limited by time or cost. To ensure that each evaluation contributes to the localization of good candidates for the role of global ...
Département Signaux +5 more
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Teamwork Optimization Algorithm: A New Optimization Approach for Function Minimization/Maximization
Sensors, 2021 Population-based optimization algorithms are one of the most widely used and popular methods in solving optimization problems. In this paper, a new population-based optimization algorithm called the Teamwork Optimization Algorithm (TOA) is presented to ...
Mohammad Dehghani, Pavel Trojovský
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BiomimeticsIn recent years, swarm intelligence optimization methods have been increasingly applied in many fields such as mechanical design, microgrid scheduling, drone technology, neural network training, and multi-objective optimization.
Wenjie Tang +4 more
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Distributed Optimization Algorithm for Composite Optimization Problems with Non-Smooth Function
Mathematics, 2022 This paper mainly studies the distributed optimization problems in a class of undirected networks. The objective function of the problem consists of a smooth convex function and a non-smooth convex function.
Yawei Shi +3 more
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AutomatikaImperialist competitive algorithm (ICA) is an efficient meta-heuristic algorithm by simulating the competitive behaviour among imperialist countries. However, it still suffers from slow convergence and deficiency in exploration.
Dongge Lei, Lulu Cai, Fei Wu
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Mathematical and Computational Applications, 2018 The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed.
Narinder Singh, Hanaa Hachimi
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Function Optimization and Parameter Performance Analysis Based on Gravitation Search Algorithm
Algorithms, 2015 The gravitational search algorithm (GSA) is a kind of swarm intelligence optimization algorithm based on the law of gravitation. The parameter initialization of all swarm intelligence optimization algorithms has an important influence on the global ...
Jie-Sheng Wang, Jiang-Di Song
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SFO: A Toolbox for Submodular Function Optimization [PDF]
, 2010 In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns property, stating that adding an element to a smaller set helps more than adding ...
Krause, Andreas
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A Novel Dynamic Generalized Opposition-Based Grey Wolf Optimization Algorithm
Algorithms, 2018 To enhance the convergence speed and calculation precision of the grey wolf optimization algorithm (GWO), this paper proposes a dynamic generalized opposition-based grey wolf optimization algorithm (DOGWO). A dynamic generalized opposition-based learning
Yanzhen Xing, Donghui Wang, Leiou Wang
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